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🚀 About WRITERWRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI.Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI.📐 About the roleAs a deployment engineer at WRITER, you'll be at the forefront of expanding human capacity through superintelligence. This isn't just a technical role; it's a deeply influential one where you'll partner directly with our leading enterprise customers. Your expertise will be crucial in uncovering their unique business challenges and architecting AI-powered solutions that leverage our powerful platform and enterprise-grade LLMs. You'll transform complex needs into tangible, high-impact applications, creating champions and driving tangible business results. Your builder's mentality and passion for bringing cutting-edge AI into the hands of real users will directly shape the future of work for some of the world's largest companies.This is a critical role that directly impacts our customers' success and product evolution. You'll contribute significantly to WRITER's mission, working with a dynamic team to push the boundaries of what's possible with generative AI.This is a hybrid role based out of London hub.🦸🏻‍♀️ What you'll doPartner deeply with enterprise customers to identify strategic AI use cases, validating technical feasibility and owning the end-to-end implementation of tailored solutionsArchitect and deliver custom applications, templates, and integrations leveraging WRITER's platform, APIs, and Knowledge Graph capabilities to solve complex business challengesTranslate intricate technical concepts and platform capabilities into clear, prescriptive solution recommendations, guiding customers through the generative AI landscapeCollaborate relentlessly with internal Product and Engineering teams, providing crucial customer feedback that directly influences our product roadmap and drives continuous innovationDrive down customer time-to-value by developing scalable processes, robust documentation, and efficient workflows for technical integrationsChampion the successful adoption and expansion of WRITER's AI solutions within customer accounts, ensuring maximum impact and return on investment⭐️ What you needOver 5 years of hands-on experience in technical SaaS roles, with at least 3 years specifically in solutions architecture, technical consulting, or technical account managementDeep technical fluency in Python and extensive experience leveraging APIs, especially in designing sophisticated prompts and understanding linguistic principles for AI applicationsProven track record of architecting and delivering complex technical solutions for Fortune 500 enterprises in a fast-paced, high-growth B2B SaaS environmentExceptional communication and executive presence, capable of simplifying complex AI concepts for diverse audiences, from technical teams to C-suite leadershipA true builder's mindset with a passion for emerging technologies, always eager to experiment, learn, and iterate in the rapidly evolving world of generative AIA relentless drive to Connect with customers and internal teams, Challenge the status status quo with innovative solutions, and Own the successful outcomes for our most strategic accounts🍩 Benefits & perks (UK full-time employees):Generous PTO, plus company holidaysComprehensive medical and dental insurancePaid parental leave for all parents (12 weeks)Fertility and family planning supportEarly-detection cancer testing through GalleriCompetitive pension scheme and company contributionAnnual work-life stipends for:Wellness stipend for gym, massage/chiropractor, personal training, etc.Learning and development stipendCompany-wide off-sites and team off-sitesCompetitive compensation and company stock options

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Who We AreWe are an applied AI lab building end-to-end software agents. We're the team behind Devin, the first AI software engineer, and Windsurf, an AI-native IDE. These products represent our vision for AI that doesn't just assist engineers, but works alongside them as a genuine teammate.Our team is small and talent-dense: world-class competitive programmers, former founders, and researchers from the frontier of AI, including Scale AI, Palantir, Cursor, Google DeepMind, and others.Role MissionMid-training sits at the seam between pre-training and post-training and is one of the highest-leverage points in the entire model pipeline. This is where raw base model capability is sharpened into something that can reason deeply, generalize reliably, and serve as the foundation that post-training builds on.You will own the late-stage training decisions that determine what our models are fundamentally capable of: data mix and quality uplift, annealing schedules, context length extension, capability injection across coding, math, and reasoning, and the synthetic data strategies that make all of it scale. This role does cross-cutting work across what is classically considered both pre-training and post-training. We don't distinguish between research and engineering; we expect both.What You'll AccomplishData Mix and Quality Uplift: Design and iterate on high-quality data mixtures for late-stage and annealing training runs. Develop principled methods for sourcing, filtering, and weighting data to sharpen model capabilities without degrading general performance.Capability Injection: Drive targeted improvements in coding, mathematics, and long-horizon reasoning through curated data strategies and training interventions. Translate research insights into measurable capability gains on our agents.Synthetic Data Research: Develop and evaluate synthetic data pipelines that generate training signal at scale. Understand the limits and failure modes of synthetic approaches and build methods that hold up in production training runs.Annealing and Schedule Design: Research and optimize multi-stage learning rate schedules, warmup strategies, and compute allocation across training phases. Understand how schedule choices interact with data distribution and model behavior.Context Length Extension: Research and implement methods for extending effective context length without degrading short-context performance. This includes positional encoding strategies, data construction, and targeted evaluation.Evaluation and Iteration: Build evals that distinguish real capability improvements from benchmark overfitting. Close the loop between training decisions and what actually matters for Devin and our other systems in deployment.Scaling and Methodology: Measure how mid-training interventions scale with compute and data. Develop new approaches when existing methods hit ceilings; we expect both rigorous empiricism and original thinking.Exceptional Candidates Have DemonstratedDeep familiarity with the LLM training pipeline end to end: pre-training data, optimization, architecture, and how mid-training and post-training interactHands-on experience with continual pre-training, annealing, or late-stage data mixing for large modelsStrong intuition for data quality: what makes a dataset useful for training, how to filter and curate at scale, and how data mix choices compound across evalsExperience developing or evaluating synthetic data pipelines for capability improvementProficiency in Python and deep learning frameworks (PyTorch); comfortable debugging distributed training at scaleStrong fundamentals in optimization, statistics, and ML theory; able to distinguish real effects from noise, instability, and overfittingA track record of original contributions: publications, open-source impact, or internal results that moved a capability frontierComfort operating in ambiguous, fast-moving environments where the problem definition is as important as the solutionWe care more about demonstrated capability than credentials. A PhD is one signal among many.Resources & EnvironmentSmall, highly selective team where research and product move together; prototypes reach real deployment quicklyCompute is not a constraint: large allocations with training jobs routinely running across thousands of GPUs from day oneThe environment rewards speed, autonomy, and technical depth with minimal process overhead; this is one of the most competitive and fast-moving problems in AI Equal OpportunityCognition is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under applicable law. We are committed to providing reasonable accommodations for candidates with disabilities throughout the hiring process - please let us know if you need any.

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About Us Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations. Each AI agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work. Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction. Why Join Us We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization. You’ll own the end-to-end lifecycle of AI agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance. What you’ll be doing Build & Deploy Agents: Own the implementation of AI agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks. Client Engagement: Act as the primary technical partner for customers—lead regular demos, communicate progress, gather feedback, and guide solutions from concept to production. Systems Integration: Configure and connect systems using APIs—handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools. Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality. Prompt Design & Optimization: Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets. Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion. Cross Functional Collaboration: Collaborate with product/engineering teams to escalate platform gaps and resolve deep technical fixes and platformization, while independently driving leading client implementations. What you’ll Bring Bachelor’s degree in Computer Science, Engineering, or a related technical field 3+ years in conversational AI, solution engineering, system integration, or delivering AI/LLM-based applications in customer environments, software engineering, or system integration with hands-on delivery of AI/LLM-based solutions. Strong ability to communicate and  lead customer-facing discussions - from deep technical troubleshooting to weekly project demos. Ability to explain complex technical concepts to non-technical audiences.  Must have strong hands-on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect, etc.). Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.). Working knowledge of retrieval-augmented generation (RAG) concepts, implementation patterns and performance optimization. Programming experience in Python, JavaScript, or similar for scripting and integrations Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems.  Experience with integration tools and Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficiency in API integrations and data flow management is a plus. Familiarity with telephony or voice systems (SIP, CCaaS, PSTN) is a plus.  Why You’ll Love It Here   Competitive compensation including equity: Market-aligned base pay, performance incentives, and meaningful equity ownership Excellent medical, dental, and vision insurance options: Comprehensive medical, dental and vision benefits for employees and eligible dependents Flexible Paid Time Off: Our unlimited, flexible PTO policy empowers you to take the time you need to recharge, maintain balance, and perform at your best. Additional Time to Recharge: 10 company holidays, an annual company-wide Winter Break, and paid parental leave to fully support life outside of work. 401(k) plan: Long-term financial planning support with tax-advantaged retirement savings Quarterly Lifestyle Spending Account: Flexible quarterly stipend to support wellness, learning and professional development, and personal growth Monthly Mobile + Internet Stipend: Support for remote and hybrid work connectivity needs Pre-tax Commuter Benefits: Tax-efficient transit and commuting support for hybrid and in-office employees Autonomy and Agency: Play a meaningful role in scaling a category-defining GenAI platform transforming the future of customer experience. Salary Range The base salary compensation range targeted for this full-time position is $108 - 170K per annum. Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives and equity (in the form of options). This salary range is an estimate, and the actual salary may vary based on the Company’s compensation practices. Our Commitment to Inclusion and Belonging Observe.AI is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. Observe AI does not make hiring or employment decisions on the basis of race, color, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other basis protected by applicable local, state, or federal laws or prohibited by Company policy. Observe.AI also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. We welcome all people. We celebrate diversity of all kinds and are committed to creating an inclusive culture built on a foundation of respect for all individuals. We seek to hire, develop, and retain talented people from all backgrounds. Individuals from non-traditional backgrounds, historically marginalized or underrepresented groups are strongly encouraged to apply. If you are ambitious, make an impact wherever you go, and you're ready to shape the future of Observe.AI, we encourage you to apply. For more information, visit www.observe.ai.  #LI- Redwood City, CA (Hybrid)

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About Liquid AISpun out of MIT CSAIL, we build general-purpose AI systems that run efficiently across deployment targets, from data center accelerators to on-device hardware, ensuring low latency, minimal memory usage, privacy, and reliability. We partner with enterprises across consumer electronics, automotive, life sciences, and financial services. We are scaling rapidly and need exceptional people to help us get there.The OpportunityLiquid AI is building a solutions architecture function from scratch. You will be one of the first SAs, working directly with the Head of Solutions Architecture and across the go-to-market org to own customer engagements end-to-end.Our models are purpose-built for environments where memory, latency, and power are binding constraints - edge devices, mobile, embedded systems, and on-prem infrastructure where frontier models simply cannot run. You will work at this boundary every day.Customers range from AI-native companies to enterprise organizations exploring AI for the first time. Your job is to bridge the gap between what our models can do and what customers believe is possible, then deliver on that promise from technical validation through go-live.What We're Looking ForWe need someone who:Technical builder: You can download a model, build a demo, and present it to a customer. You are as comfortable in a Jupyter notebook as you are in a boardroom.Creative problem solver: You see opportunities where customers see limitations. You can take a small, efficient model and show an enterprise why it changes their cost structure or enables something they did not think was possible.End-to-end owner: You do not draw a line between 'pre-sales' and 'post-sales.' You own the outcome from first call to go-live and beyond.Org builder: You want to build a function, not inherit one. You will create playbooks, demo libraries, and engagement processes that scale as the team grows.Imagination-gap closer: Enterprise buyers often cannot envision what a fine-tuned small model can do at middleware speeds. You don't just demo—you reframe what's possible on hardware they already own.The WorkOwn customer engagements end-to-end: from qualified opportunity through technical validation, go-live, and ongoing delivery across all customer segmentsBuild customer-specific demos and proofs-of-concept using Liquid models (including LEAP for fine-tuning, domain adaptation, and evaluation) to drive technical winsLead technical discovery: map current-state customer architectures to Liquid solutions, drive competitive positioning against open-source and incumbent models, and quantify ROI for both cost-optimization and new-experience use casesCo-own the product-field feedback loop: document friction patterns, eval failures, and capability gaps from engagements and partner with product and research to influence roadmapTurn engagement learnings into reusable assets: reference architectures, solution primitives, demo building blocks, engagement playbooks, and vertical-specific solution patterns across Liquid's priority industriesDesired ExperienceMust-have:Applied ML skills: hands-on experience working with ML models in customer-facing contexts (building demos, prototypes, or production integrations)Pre-sales and post-sales experience: you have owned technical customer engagements end-to-end, not just the pitchStrong customer-facing communication: you can run discovery, build relationships with technical and business buyers, and present to executivesUnderstanding of AI architectures and deployment tradeoffs: token efficiency, on-device vs. cloud, model size vs. latency, open-weight vs. proprietaryNice-to-have:Familiarity with small or efficient model deployment (edge, on-device, latency-constrained environments)Track record of creating thought leadership content, technical blogs, or presenting at industry eventsFamiliarity with efficient model deployment: quantization (INT4/INT8, GGUF, AWQ), model serving frameworks (vLLM, TensorRT-LLM, llama.cpp), and hardware-aware optimization for edge or latency-constrained environmentsExperience designing and debugging model evaluations—you understand why benchmark results can diverge from production performance and know how to diagnose the root causeWhat Success Looks Like (Year One)Qualified opportunities convert to technical wins faster, with a measurable improvement in the qualified-to-win rateA library of scalable demos, engagement playbooks, and customer-facing collateral exists and is actively usedA structured feedback loop from customer conversations to the product and model teams is established and influencing roadmap decisionsWhat We OfferBuild the function: You are defining how Liquid goes to market technically, with direct influence on product direction and access to the founding team.Compensation: Competitive base salary with equity in a unicorn-stage companyHealth: We pay 100% of medical, dental, and vision premiums for employees and dependentsFinancial: 401(k) matching up to 4% of base payTime Off: Unlimited PTO plus company-wide Refill Days throughout the year

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About usAt Sierra, we’re creating a platform to help businesses build better, more human customer experiences with AI. We are primarily an in-person company based in San Francisco, with growing offices in Atlanta, New York, London, Paris, Madrid, Munich, Singapore, Japan, and Sydney.We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are committed to upholding them in everything we do.Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. What you’ll doDesign and deliver production-grade AI agents: You'll build and ship highly performant, reliable, and intuitive AI agents that are central, mission-critical and drive revenue directly to Sierra's growth. These aren't prototypes—they are powerful, scalable systems running in production environments across industries like finance, healthcare, and commerce.Drive the Agent Development Life Cycle (ADLC): You'll have complete ownership and autonomy from initial pilot through deployment and continuous iteration. You'll be responsible for building, tuning, and evolving AI agents in production environments, defining the standard for ADLC best practices along the way.Partner with large enterprises and cutting-edge startups: You’ll work directly with leaders at some of the world’s largest enterprises to understand their most pressing business challenges, and build AI agents that transform how they operate at scale. You'll also partner with the most cutting-edge startups, embedding AI agents across their entire business stack to drive innovation and efficiency.Build the future of the platform: Your direct work with customers will guide the evolution of Sierra's core platform. You'll surface unmet needs, prototype new tools and features, and collaborate with research, product, and platform to shape the future of AI agent development and Sierra's product.Example projectsThese are some examples of projects that engineers on our team have worked on recently:Design and build AI agents for large telecommunications and media companies that consistently outperform human agents in managing subscription churnDevelop and refine AI agents capable of navigating complex customer interactions, like troubleshooting a broken device and personalizing product recommendationsCreate generalizable AI agent frameworks tailored for industry-specific use cases. See some examples in our financial services blog!Facilitate design partnerships for new product initiatives, such as new agent architectures, self-service capabilities, and generative agent developmentExperiment with the latest voice models and figure out how to integrate them at scale to enterprise-grade customersWhat you'll bringExperience building and scaling end-to-end production systemsStrong technical problem-solving skills, especially in fast-changing, ambiguous environmentsA builder and tinkerer’s mindset with high agency - you find creative ways to overcome obstacles and shipComfort working directly with customers to understand their needs and solve real-world problemsExcellent communication skills - clear, direct, and persuasive across technical and non-technical audiencesEven better...Experience building or deploying AI/LLM systems in productionHave been a founder or founding engineer - you know what it means to balance craft, ownership, and speedFamiliarity with tools that power today's AI agents: eval frameworks, agent tooling, RAG pipelines, and prompt engineeringPrior experience with React, TypeScript, and/or GoPrevious roles where you interfaced with customers or led technical projects with external stakeholdersOur valuesTrust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.What we offerWe want our benefits to reflect our values and offer the following to full-time employees:Flexible (Unlimited) Paid Time OffMedical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension) with Sierra matchParental LeaveFertility and family building benefits through CarrotLunch, as well as delicious snacks and coffee to keep you energized Discretionary Benefit Stipend giving people the ability to spend where it matters mostFree alphorn lessonsThese benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.Be you, with usWe're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

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The AI orchestration of your wildest imagination.n8n is the open workflow orchestration platform built for the new era of AI. We give technical teams the freedom of code with the speed of no-code, so they can automate faster, smarter, and without limits. Backed by a fiercely inventive community and 500+ builder-approved integrations, we’re changing the way people bring systems together and scale ideas for impact.Since our founding in 2019, we’ve grown into a diverse team of over 220 - working across Europe and the US, connected by a shared builder spirit and with our centre of gravity in Berlin. Along the way, we’ve:Cultivated a community of more than 650,000 active developers and buildersEarned 145k+ GitHub stars, making us one of the world’s Top 40 most popular projectsBeen ranked as one of Europe’s most promising privately held SaaS startups (4th in Sifted’s 2025 B2B SaaS Rising 100)Raised $240m to date, from Sequoia’s first German seed to our recent $180m Series C - bringing us to a $2.5bn valuation That’s the company we’ve built. Now we’d love to see what you can build. If you’re applying, try n8n out - whether you’re technical or not - and share a screenshot of your first workflow with us. The easiest place to start is here: app.n8n.cloud/register.We’re in a defining moment of an incredible journey. Come and build with us.AI Engineering Manager Your main goal will be to build and lead an engineering team that thrives in a fast-moving agentic, AI-native world—developing engineers, creating clarity, and delivering meaningful outcomes with strong technical judgment. This is a first-line engineering leadership role for someone who is deeply technical, but whose real strength is building teams: empowering engineers on their growth path, aligning stakeholders, and helping people move with confidence as AI agents, workflow automation, and user expectations evolve rapidly. You will lead teams working on AI agents and agentic workflows within n8n, enabling users to orchestrate complex, multi-step automation across tools, data, and models. This includes shaping how LLMs, tools, APIs, and workflows come together into reliable, composable systems that users can trust in production. Build an empowered, high-performing AI agent & evaluation team • Lead, coach, and develop a team of engineers building agent-based systems, workflow orchestration capabilities, and AI-powered nodes. • Foster a culture of experimentation and rapid iteration, where engineers continuously improve prompts, tool usage, and workflow logic based on real-world outcomes. • Help your team think in terms of systems, not features—designing reliable agentic workflows rather than one-off AI calls. • Support hiring and team shaping with a focus on AI engineering, distributed systems thinking, and product-minded builders. Create clarity in an agentic, fast-evolving landscape • Help your team navigate a space where agents, tools, memory, and orchestration patterns are still emerging and rapidly changing. • Translate evolving AI capabilities into clear product and engineering direction for n8n workflows, nodes, and automation primitives. • Guide decisions around agent architecture (e.g., single-agent vs multi-agent workflows, tool selection, memory strategies, human-in-the-loop design). • Cut through hype and ambiguity to focus on what delivers real, reliable value to users building automations. Drive execution of agentic workflows at scale • Partner with Product and Design to define and ship agent-powered workflow experiences that feel intuitive, composable, and powerful. • Ensure the team delivers end-to-end agent systems, including orchestration logic, tool integrations, memory handling, and execution environments. • Establish best practices for workflow reliability, including retries, fallbacks, guardrails, and observability of agent behaviour. • Balance speed and iteration with the need for determinism, debuggability, and user trust in automated systems. • Drive improvements in how users build, test, and debug AI-powered workflows inside n8n. Lead with technical credibility in agent systems • Bring strong technical depth in LLM integrations, tool use, and workflow orchestration, enabling you to mentor and challenge your team. • Support architectural decisions around agent frameworks, execution engines, state management, and integration layers. • Help the team design systems that handle long-running workflows, external APIs, and dynamic decision-making by agents. • Step into technical details when needed (e.g., prompt design, tool schemas, workflow execution issues) to unblock the team. • Promote best practices around safety, guardrails, and predictable behaviour in agent-driven systems. REQUIREMENTS Must-havesFirst-line engineering management experience: You’ve led teams delivering meaningful product outcomes, ideally including automation platforms, workflow systems, or AI-powered features. Significant experience working with Evaluations & driving results via evals. Strong people leadership: You coach engineers effectively and build teams that thrive in ambiguous, fast-evolving technical spaces.Comfort with ambiguity and speed: You bring clarity in a world where agent patterns, tooling, and best practices are still emerging. • Strong software engineering background: You can confidently engage in discussions around distributed systems, APIs, and system design. • Hands-on when needed: You can dive into workflow logic, integrations, or AI system behaviour to support your team. • Cross-functional alignment: Experience working closely with Product and Design to deliver end-user-facing builder experiences. • High-growth SaaS experience: You understand how to scale teams and systems in a fast-moving environment. • AI/agent exposure: Experience working with LLMs, agents, or automation systems, with an understanding of their strengths, limitations, and failure modes. Nice-to-haves • n8n or workflow tooling familiarity: Experience with n8n or similar automation platforms. • Integration-heavy systems: Background in building or scaling API-driven platforms or extensible systems. • Deep agent experience: Hands-on work with agent frameworks, tool use, memory systems, or multi-step reasoning workflows. • Observability & debugging: Experience building tools for inspecting, debugging, and improving complex workflows or AI systems. • Responsible AI: Awareness of guardrails, failure handling, and safe automation practices in user-facing AI systems.Why join us?At n8n, you’ll join at a moment where strong engineering leadership can have outsized impact. We’re building in a space that is moving quickly, and we see that as an opportunity: to help teams stay ambitious, grounded, and effective while shaping what great engineering leadership looks like in an AI-native company. You’ll play a key role in building teams that empower others, act with integrity, move with speed and efficiency, and think bigger than incremental improvement. In a remote-first company growing fast, your work will directly influence how we scale our engineering organization and build the future of automation.n8n is an equal opportunity employer and does not discriminate on the basis of race, religion, colour, national origin, gender, sexual orientation, gender identity, age, marital status, veteran status, or disability status.We can sponsor visas to Germany; for any other country, you need to have existing right to work.Our company language is English.You care about diversity and inclusion? We do too! Check out our Diversity, Inclusion and Belonging initiatives at n8n (https://www.notion.so/n8n/Diversity-inclusion-and-belonging-n8n-c1bec2fff536422d868b1a438d990e35).Location disclaimer: If you see multiple job postings for the same role, it is most likely because we're hiring remotely for this role and posting in different locations to make sure every potential candidate can see the role. Please apply to the location you're the most likely to work from in the future. Benefits Competitive compensation 💸 – We offer fair and attractive pay.Ownership 💪 – Our core value is to “empower others,” and we mean it—you’ll get a slice of n8n with equity.Work/life balance 🏖️ – We work hard but ensure you have time to recharge:Europe: 30 days of vacation, plus public holidays wherever you are.US: 20 vacation days, 8 sick days, plus public holidays wherever you are.Health & wellness 🩺 –Europe: We provide benefits according to local country norms.*US: Multiple low-premium, low-deductible medical plans with coverage for individuals and families—plus a no-cost premium HDHP option with a pre-seeded HSA—along with dental and vision coverage.Future planning 💰 –Europe: We provide pension contributions according to local country norms.*US: 401(k) retirement plan with a 4% employer match.Financial security 🛡️ –Europe: We provide benefits according to local country norms.*US: Company-paid short-term and long-term disability insurance, plus life insurance to support you and your loved ones.Career growth 📈 – We hire rising stars who grow with us! You’ll get €1K (or equivalent) per year to spend on courses, books, events, or coaching to level up your skills.A passionate team 🤩 – We love our product, and we prove it with regular hackathons where we see who can build the coolest thing with it!Remote-first 🌏 – Our team works remotely across Europe, with regular off-sites for team bonding. Some roles, like sales in the US, are hybrid—please check the job description.Giving back 🤝 – We're big fans of open source, and you'll get $100 per month to support projects you care about.AI enablement 🤖 – We believe in working smarter—everyone gets an unlimited AI budget to explore and use the best tools to boost productivity and creativity.Transparency 🙏 – We all know what everyone’s working on, how the company is doing—the whole shebang.An ambitious but kind culture 😍 – People love working here—our eNPS for 2024 is 94!* Country-specific details are provided in your contract.

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Shape the Future of AI At Labelbox, we're building the critical infrastructure that powers breakthrough AI models at leading research labs and enterprises. Since 2018, we've been pioneering data-centric approaches that are fundamental to AI development, and our work becomes even more essential as AI capabilities expand exponentially. About Labelbox We're the only company offering three integrated solutions for frontier AI development: Enterprise Platform & Tools: Advanced annotation tools, workflow automation, and quality control systems that enable teams to produce high-quality training data at scale Frontier Data Labeling Service: Specialized data labeling through Alignerr, leveraging subject matter experts for next-generation AI models Expert Marketplace: Connecting AI teams with highly skilled annotators and domain experts for flexible scaling Why Join Us High-Impact Environment: We operate like an early-stage startup, focusing on impact over process. You'll take on expanded responsibilities quickly, with career growth directly tied to your contributions. Technical Excellence: Work at the cutting edge of AI development, collaborating with industry leaders and shaping the future of artificial intelligence. Innovation at Speed: We celebrate those who take ownership, move fast, and deliver impact. Our environment rewards high agency and rapid execution. Continuous Growth: Every role requires continuous learning and evolution. You'll be surrounded by curious minds solving complex problems at the frontier of AI. Clear Ownership: You'll know exactly what you're responsible for and have the autonomy to execute. We empower people to drive results through clear ownership and metrics. Role Overview As an Applied Research Engineer at Labelbox, you will be at the forefront of developing cutting-edge systems and methods to create, analyze, and leverage high-quality human-in-the-loop data for frontier model developers. Your role will involve designing and implementing advanced systems that align human feedback into AI training processes, such as Reinforcement Learning from Human Feedback (RLHF), Direct Preference Optimization (DPO), etc. You will also work on innovative techniques to measure and improve human data quality, and develop AI-assisted tools to enhance the data labeling process. Your expertise in machine learning, frontier model training, and advanced human data alignment techniques will be crucial in pushing the boundaries of AI capabilities and delivering state-of-the-art solutions to meet the evolving needs of our customers. Your Impact Advance the field of AI alignment by developing cutting-edge methods, such as RLHF and novel approaches, that ensure AI systems reflect human preferences more accurately. Improve the quality of human-in-the-loop data by designing and deploying rigorous measurement and enhancement systems, leading to more reliable AI training. Increase efficiency and effectiveness in AI-assisted data labeling by creating tools that leverage active learning and adaptive sampling, reducing manual effort while improving accuracy. Shape the next generation of AI models by investigating how different types of human feedback (e.g., demonstrations, preferences, critiques) impact model performance and alignment. Optimize human feedback collection by developing novel algorithms that enhance how AI learns from human input, improving model adaptability and responsiveness. Bridge research and real-world application by integrating breakthroughs into Labelbox’s product suite, making human-AI alignment techniques scalable and impactful for users. Drive industry innovation by engaging with customers and the broader AI community to understand evolving data needs and share best practices for training frontier models. Contribute to the AI research ecosystem by publishing in top-tier journals, presenting at leading conferences, and influencing the future of human-centric AI. Stay ahead of AI advancements by continuously exploring new frontiers in human-AI collaboration, human data quality, and AI alignment, keeping Labelbox at the cutting edge. Establish Labelbox as a thought leader in AI by creating technical documentation, blog posts, and educational content that shape the industry's approach to human-centric AI development. What You Bring A strong foundation in AI and machine learning, backed by a Ph.D. or Master’s degree in Computer Science, Machine Learning, AI, or a related field. Proven experience (3+ years) in solving complex ML challenges and delivering impactful solutions that improve real-world AI applications. Expertise in designing and implementing data quality measurement and refinement systems that directly enhance model performance and reliability. A deep understanding of frontier AI models—such as large language models and multimodal models—and the human data strategies needed to optimize them. Proficiency in Python and experience with deep learning frameworks like PyTorch, JAX, or TensorFlow to prototype and develop cutting-edge solutions. A track record of publishing in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL) and contributing to the broader research community. The ability to bridge research and application by interpreting new findings and rapidly translating them into functional prototypes. Strong analytical and problem-solving skills that enable you to tackle ambiguous AI challenges with structured, data-driven approaches. Exceptional communication and collaboration skills, allowing you to work effectively across multidisciplinary teams and with external stakeholders. Labelbox Applied Research At Labelbox Applied Research, we're committed to pushing the boundaries of AI and data-centric machine learning, with a particular focus on advanced human-AI interaction techniques. We believe that high-quality human data and sophisticated human feedback integration methods are key to unlocking the next generation of AI capabilities. Our research team works at the intersection of machine learning, human-computer interaction, and AI ethics to develop innovative solutions that can be practically applied in real-world scenarios. We foster an environment of intellectual curiosity, collaboration, and innovation. We encourage our researchers to explore new ideas, engage in open discussions, and contribute to the wider AI community through publications and conference presentations. Our goal is to be at the forefront of human-centric AI development, setting new standards for how AI systems learn from and interact with humans.Labelbox strives to ensure pay parity across the organization and discuss compensation transparently.  The expected annual base salary range for United States-based candidates is below. This range is not inclusive of any potential equity packages or additional benefits. Exact compensation varies based on a variety of factors, including skills and competencies, experience, and geographical location.Annual base salary range$250,000—$300,000 USDLife at Labelbox Location: Join our dedicated tech hubs in San Francisco or Wrocław, Poland Work Style: Hybrid model with 2 days per week in office, combining collaboration and flexibility Environment: Fast-paced and high-intensity, perfect for ambitious individuals who thrive on ownership and quick decision-making Growth: Career advancement opportunities directly tied to your impact Vision: Be part of building the foundation for humanity's most transformative technology Our Vision We believe data will remain crucial in achieving artificial general intelligence. As AI models become more sophisticated, the need for high-quality, specialized training data will only grow. Join us in developing new products and services that enable the next generation of AI breakthroughs. Labelbox is backed by leading investors including SoftBank, Andreessen Horowitz, B Capital, Gradient Ventures, Databricks Ventures, and Kleiner Perkins. Our customers include Fortune 500 enterprises and leading AI labs. Your Personal Data Privacy: Any personal information you provide Labelbox as a part of your application will be processed in accordance with Labelbox’s Job Applicant Privacy notice. Any emails from Labelbox team members will originate from a @labelbox.com email address. If you encounter anything that raises suspicions during your interactions, we encourage you to exercise caution and suspend or discontinue communications.

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About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence. We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.Note: The nature of this role requires candidates to be based in the Buenos Aires area, though there isn't an in-office requirement. The Opportunity We’re looking for an Application Engineer who thrives on solving hard problems with code. In this role, you'll have the opportunity to work at the cutting edge of generative AI in a high-impact role with autonomy and ownership. What You’ll Do Debug and fix issues in our platform (and ship PRs with your fixes). Build internal tools and copilots powered by generative AI to supercharge our team. Rapidly prototype proof-of-concepts for customer use cases. Work across Engineering, Product, and Solutions to unblock customers and push the boundaries of AI adoption. What We’re Looking For You have 2-5 years of experience in software. Strong in Python and Golang; comfortable shipping fixes in production systems. Hands-on with generative AI (LLM APIs, frameworks, building copilots or automations) Hands-on with OpenTelimetry and deep familiarity with distributed tracing concepts. Familiarity with AI frameworks (CrewAI, Langchain, Langgraph, DiFy, LiteLLM, etc). Familiarity or eagerness to learn JavaScript/TypeScript. Great debugger, creative problem solver, and fast learner. Independent and resourceful. You create solutions, not dependencies. Bonus Points (but not required!) Experience in a customer-facing role Built copilots, plugins, or custom GenAI-powered applications. Open-sourced or contributed PRs to real codebases. Startup or fast-moving environment experience. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes unlimited paid time off, generous parental leave plan, and others for mental and wellness support.More About Arize Arize’s mission is to make the world’s AI work—and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/ https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/ Diversity & Inclusion @ Arize Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI Culturally conscious events such as LGBTQ trivia during pride month We have an active Lady Arizers subgroup

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About usAt Sierra, we’re creating a platform to help businesses build better, more human customer experiences with AI. We are primarily an in-person company based in San Francisco, with growing offices in Atlanta, New York, London, Paris, Madrid, Munich, Singapore, Japan, and Sydney.We are guided by a set of values that are at the core of our actions and define our culture: Trust, Customer Obsession, Craftsmanship, Intensity, and Family. These values are the foundation of our work, and we are committed to upholding them in everything we do.Our co-founders are Bret Taylor and Clay Bavor. Bret currently serves as Board Chair of OpenAI. Previously, he was co-CEO of Salesforce (which had acquired the company he founded, Quip) and CTO of Facebook. Bret was also one of Google's earliest product managers and co-creator of Google Maps. Before founding Sierra, Clay spent 18 years at Google, where he most recently led Google Labs. Earlier, he started and led Google’s AR/VR effort, Project Starline, and Google Lens. Before that, Clay led the product and design teams for Google Workspace. About the roleWe’re looking for a Product Manager for Ghostwriter: the agent-building agent.Ghostwriter transforms how software is built. Instead of navigating tools, users simply describe what they want, and Ghostwriter creates and deploys fully functional AI agents across channels like chat, voice, and email.As PM for Ghostwriter, you will define how humans interact with software in the agent era. You’ll own the end-to-end product experience—from prompt → agent → outcome—and help scale Sierra to thousands of customers.This is a zero-to-one and one-to-many role at the same time.What you'll doDefine how AI augments agent development — shape the workflows by which CX teams and developers draft journeys, run simulations, analyze conversations, and improve agents using natural language.Balance autonomy and control — design the right human-in-the-loop patterns (approval flows, change review, workspace isolation) so customers trust Ghostwriter to make meaningful changes to their agents.Partner deeply with AI/ML and platform engineering — collaborate on model selection, harness engineering, execution architecture, and evaluation/testing infrastructure.Be the voice of the agent builder — deeply understand the pain points of CX managers, agent developers, and technical teams configuring journeys, integrations, and simulations.What you'll bring3+ years of product management experience, with meaningful time working with large language models directly.Experience shipping AI products at the frontier — you deeply understand frontier model capabilities and limitations, evaluation challenges, and the unique UX considerations of non-deterministic systems.Track record of 0→1 product development — you've taken an early-stage product and driven it to broad adoption; comfortable with high ambiguity and rapid iteration.Strong technical depth — ability to engage meaningfully with engineers on architecture decisions (e.g., harness design and engineering, workspace isolation, API design).Our valuesTrust: We build trust with our customers with our accountability, empathy, quality, and responsiveness. We build trust in AI by making it more accessible, safe, and useful. We build trust with each other by showing up for each other professionally and personally, creating an environment that enables all of us to do our best work.Customer Obsession: We deeply understand our customers’ business goals and relentlessly focus on driving outcomes, not just technical milestones. Everyone at the company knows and spends time with our customers. When our customer is having an issue, we drop everything and fix it.Craftsmanship: We get the details right, from the words on the page to the system architecture. We have good taste. When we notice something isn’t right, we take the time to fix it. We are proud of the products we produce. We continuously self-reflect to continuously self-improve.Intensity: We know we don’t have the luxury of patience. We play to win. We care about our product being the best, and when it isn’t, we fix it. When we fail, we talk about it openly and without blame so we succeed the next time.Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other and celebrate each other’s personal and professional achievements.What we offerWe want our benefits to reflect our values and offer the following to full-time employees:Flexible (Unlimited) Paid Time OffMedical, Dental, and Vision benefits for you and your familyLife Insurance and Disability BenefitsRetirement Plan (e.g., 401K, pension) with Sierra matchParental LeaveFertility and family building benefits through CarrotLunch, as well as delicious snacks and coffee to keep you energized Discretionary Benefit Stipend giving people the ability to spend where it matters mostFree alphorn lessonsThese benefits are further detailed in Sierra's policies, may vary by region, and are subject to change at any time, consistent with the terms of any applicable compensation or benefits plans. Eligible full-time employees can participate in Sierra's equity plans subject to the terms of the applicable plans and policies.Be you, with usWe're working to bring the transformative power of AI to every organization in the world. To do so, it is important to us that the diversity of our employees represents the diversity of our customers. We believe that our work and culture are better when we encourage, support, and respect different skills and experiences represented within our team. We encourage you to apply even if your experience doesn't precisely match the job description. We strive to evaluate all applicants consistently without regard to race, color, religion, gender, national origin, age, disability, veteran status, pregnancy, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.

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The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Model Optimization & Deployment Engineer, you will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience in compressing, accelerating, and deploying complex models (LLMs, VLMs, or FMs) for power- and thermal-constrained vehicle SOCs. You will optimize the ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices.In this role, you will: Optimize large-scale models (LLMs, VLMs) using advanced quantization (PTQ, QAT), mixed-precision inference workflows, and parameter-efficient fine-tuning (LoRA, QLoRA). Architect and implement model conversion and compilation pipelines using TensorRT and TensorRT-LLM for edge deployment. Perform rigorous parity checking, accuracy recovery, and latency benchmarking between PyTorch frameworks and compiled edge binaries. Write and optimize custom CUDA kernels and TensorRT Plugins to maximize memory bandwidth and minimize latency on AI accelerators. Write production-level, highly concurrent, and memory-safe C++ and Python code for real-time inference on vehicle SOCs. Qualifications: Deep expertise in model quantization (PTQ, QAT) and mixed-precision inference workflows (INT8, FP8, INT4, BF16/FP16). Proven experience optimizing large-scale models (LLMs, VLMs, or VLAs) utilizing KV-cache optimization (e.g., PagedAttention), Speculative Decoding, and Efficient Attention mechanisms (FlashAttention, Linear Attention). Extensive experience with model conversion/compilation pipelines (TensorRT, TensorRT-LLM) and performing rigorous parity/latency benchmarking. Proficiency in low-level programming for AI accelerators, specifically writing and optimizing custom CUDA kernels and TensorRT Plugins. Production-level C++ (14/17/20) and Python programming skills, with experience writing concurrent, memory-safe, real-time inference code for edge devices. Bonus Qualifications: Experience with distributed training pipelines and model/tensor parallelism (PyTorch Distributed, Ray, DeepSpeed, Megatron-LM) and runtime efficiency optimization for GPU clusters. Familiarity with autonomous driving perception stacks (temporal 3D object detection, BEV, 3D Occupancy Networks) and processing multi-modal sensor streams (Vision, LiDAR, Radar). Understanding of end-to-end autonomous driving paradigms (VLA models, closed-loop simulation validation). 242,000 - 290,000 a year Base Salary Range   There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.   Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance. About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

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Do you get excited when your software actually interacts with the physical world?  Are you ready to learn the new exciting world of smart robots? Do you feel tired of working in a big company? Would you like to cooperate with top professionals in our industry? If your answers are mostly yes, then you should keep reading.  At Nomagic, we’re on a mission to teach robots the real world. We’re now looking for a Senior Robotics/Software Engineer - Grippers R&D, who’s ready to deep dive into the hard problems of physical manipulation (trying to match with software the millions of years of development leading to the human hand + eye) and share his software development and design experience with our amazing team. Offer essentials: Play with robots every day! Salary: 26 000 - 32 000 gross UoP per month + equity Equity for every employee Relocation package  Truly flexible working hours  English-speaking environment Partly remote work is possible! Here is why we love this job ourselves, and hope you will enjoy it too: We build robots powered by AI We have them in production at scale and see their real impact on critical operations. We test our code in unit tests, simulations and on real robots! We’re still pretty small, so everyone has a direct impact on the final result Our team has built Google Warsaw, unicorn startups (Climate Corp), tested rocket engines and worked at top companies such as Nvidia or ByteDance. Now we shape the future of smart robotics together! We combine world-class research with top notch engineering and apply it to solve real problems Some of the problems you may try to solve with us: Building the best-in-the-world objects manipulation system with cross-functional R&D team (Hardware, Software & AI) Inventing and implementing strategies for using new robotic grippers, handling previously unpickable items Improving adaptability, scalability & reliability of robotic platform  Using data to build heuristics for handling different categories of items Detecting anomalies, e.g. using a combination of signals to determine if a robot picked more than one item at once or if one item is disassembling What skills we'd like you to have: 3+ years of experience in software development 3+ years of experience in robotics (manipulators, AGV’s, UAV’s, sensors) Great problem solving and proficiency in one of modern programing languages (we use Python) Experience in designing systems spanning software and hardware components Great understanding of physics principles related to objects manipulation  Wide range of mechatronics knowledge, from mechanical design principles to AI image processing Fluent communication in English What should you expect once you apply? 60 minutes Technical prescreen 45 minutes Hiring Manager interview Onsites - half a day of interviews & discussions at the office  See a short sneak peek of our product here:   https://vimeo.com/manage/videos/1051464045 https://vimeo.com/manage/videos/1051465112    

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ABOUT US:Brisk Teaching is the leading AI platform for K-12 educators, empowering teachers to deliver personalized, curriculum-aligned instruction at scale. Our Classroom Intelligence tools connect teachers, students, and curriculum—making meaningful learning happen in classrooms every day. We believe the best technology is cutting-edge, respects teachers’ time, integrates into real classrooms, and helps educators focus on what matters most.Since launching, Brisk has experienced rapid growth. Over 2 million teachers use our platform, and we partner with districts and schools nationwide to transform how educators teach and how students learn.We're backed by leading venture and edtech investors including Bessemer Venture Partners (Shopify, LinkedIn, Anthropic, Perplexity) and Owl Ventures (Newsela, Quizlet, MasterClass), with a team spanning top AI companies and real classroom experience.We're a fast-moving, collaborative team driven by a shared commitment to educator impact and product excellence. Our values—urgency, ownership, and focus—shape how we build and who we are.THE OPPORTUNITY:We've already started building something we think fundamentally rethinks how data science gets done at a company. We have an internal data agent that can query our warehouse, interpret results, and surface insights to stakeholders directly. It works. People use it. And it's changed how our team operates day to day.Now we need someone to take it further. As Brisk's product and organization grow, the systems underneath need to grow with them: a more robust semantic layer, better tooling for experimentation, more sophisticated automation across the data lifecycle, and the strategic thinking to decide where AI amplifies the team's work and where it replaces manual processes entirely.This role is equal parts strategy and execution. You'll own the vision for how data drives decisions across Brisk, scale the AI-native workflows we've started, and build the systems that turn a small data team into one that operates like a much larger org. You'll report directly to leadership and have a seat at the table on product strategy, go-to-market, and company priorities.YOU WILL:Set the data strategy: Define what we measure, how we measure it, and what "good" looks like. Establish the metrics architecture that connects product usage, retention, monetization, and growth into a coherent picture, and make sure every team at Brisk is oriented around it.Turn the data team into a product team: Build internal data products that stakeholders across the company actually use daily. Replace ad-hoc requests with self-serve AI interfaces, automated reports, and tools that make data accessible to non-technical teammates.Make the warehouse AI-readable: Build the semantic layer, documentation, and context infrastructure that lets both humans and AI systems query Brisk's data accurately. A well-documented warehouse is the foundation for every AI-powered workflow that follows.Build AI into the data lifecycle: Identify where AI agents, automated pipelines, and LLM-powered tooling can replace manual work: dbt model generation, data quality monitoring, experiment analysis, insight delivery. Ship these systems into production.Own product analytics and experimentation: Partner with Product, Engineering, and Design to design experiments, interpret results, and deliver the insights that shape what we build. Bring rigor to how we evaluate features and make ship/no-ship decisions.Drive growth and business intelligence: Maintain and evolve dashboards and reporting for Sales, Marketing, Customer Success, and leadership. Ensure the metrics that matter are visible, trusted, and actionable.Scale through systems, not headcount: Build infrastructure and AI-powered tooling that multiplies the team's output so a small data org can support a fast-growing company without scaling linearly.YOU HAVE:8+ years of experience in data science, analytics engineering, or a related role. You've operated across the full analytics lifecycle and seen what works (and what doesn't) at scale.Comfort with ambiguity and speed: You've worked at a startup or similar environment where priorities shift fast, resources are limited, and scrappiness is a survival skill. You don't need a playbook to get started.Strategic instincts: You identify which questions matter, not just answer the ones you're given. You've partnered with product and business leaders to shape roadmaps, define success metrics, and make hard tradeoffs.Deep SQL and warehouse expertise: You think in SQL. You've built and maintained data models, designed schemas, and know what it takes to keep a warehouse clean, documented, and trustworthy.Pipeline and infrastructure experience: You've built data pipelines and dealt with data quality issues firsthand. You understand the plumbing as well as the dashboards.dbt experience: You've built and maintained production dbt models: transformations, testing, documentation. You understand how a well-structured dbt project makes everything downstream better.Strong product sense: You've worked closely with product teams, you understand what drives user behavior in software (ideally in edtech or SaaS), and you have good instincts for what to measure and what to build.Enough engineering chops to ship: You can build a working tool in Python, wrangle APIs, and write code that other people can maintain. You're not a SWE, but you're not afraid of production.Genuine excitement about AI: You've been building with LLMs. You have opinions about which models are good at what, you've experimented with agents or RAG systems, and you believe AI is going to fundamentally change how data teams operate.Builder mentality: You see a manual process and you can't help but automate it. You ship fast, iterate, and care more about impact than perfection.BONUS:Experience with Snowflake.Background in edtech or K-12 education.Experience building internal tools (Slack bots, CLI tools, self-serve interfaces) that people actually used.A/B testing and experimentation design.Experience managing or mentoring data team members.Early-stage startup experience where you've built a data function from the ground up.WHAT WE OFFER:Competitive salaryStock options, vested over 4 yearsComprehensive benefits package, including health, dental, and vision insurance.Opportunities for professional growth and development.Collaborate with your teammates two times a week via our hybrid model in either our San Francisco or New York City offices.A supportive and collaborative work environment.The chance to make a meaningful impact on education through innovative technology.Equal Employment Opportunity & DiversityAt Brisk, we believe that diverse perspectives make better teams and stronger products. We are an equal opportunity employer and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, disability, or any other legally protected status.

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  About the Company Armada is a full-stack edge infrastructure company delivering compute, connectivity, and sovereign AI/ML to some of the world’s most remote places. Named one of Fast Company's Most Innovative Companies, Armada’s solutions are deployed in over 60 countries globally for organizations ranging from energy to defense.    With over $200 million in funding, Armada is backed by top investors such as Microsoft (M12), Founders Fund, and has strategic partnerships including Starlink, Skydio, and NVIDIA. We are looking for the most brilliant minds in the world to join us.    Working at Armada means taking ownership, driving autonomy, and delivering impact. You’ll tackle challenges that haven’t been solved before and help build something transformative from the ground up. What you do here will not only define your career but help further Armada’s mission to bridge the digital divide for customers around the world.      About the role At Armada, we are unlocking the limitless potential of AI to transform operations and improve lives in some of the most remote locations on Earth. From the expansive mines of Australia to the oil fields of Northern Canada, and the coffee plantations of Colombia, Armada offers a unique opportunity to tackle exciting AI and ML challenges on a global scale. We are actively seeking passionate AI Engineers with hands-on expertise across a range of domains, including real-time computer vision, statistical machine learning, natural language processing, transformers, control and navigation, reinforcement learning, and large-scale distributed AI systems. Ideal candidates will possess strong skills in machine learning (ML), deep learning (DL), and real-time computer vision techniques. You will be responsible for building ML/DL models tailored to specific challenges, preparing datasets for testing, evaluating model performance, and deploying solutions in production environments. Familiarity with containerization, microservices architecture, and the ability to independently deploy ML models into production is essential. If you are a self-driven individual with a passion for cutting-edge AI, we want to hear from you. Armada offers an unparalleled opportunity to confront some of the most thrilling AI and ML challenges in the world. Join our dynamic AI Engineering team as we deliver disruptive edge-compute systems capable of autonomous learning, prediction, and adaptation using vast, real-time datasets. We are pioneers in developing high-performance computing solutions for self-driving cars, camera networks, robotics, drones, conversational agents, and real-time monitoring and diagnostic systems. Our vision is to empower AI systems to seamlessly and securely interact with the complexities and uncertainties of the real world, and our mission is to bridge the digital divide in the process.  Location. This role is office-based at our Bellevue, Washington office.  What You'll Do (Key Responsibilities) Translating business requirements into requirements for AI/ML models. Preparing data to train and evaluate AI/ML/DL models. Building AI/ML/DL models by applying state-of-the-art algorithms, especially transformers. In some cases, leverage existing algorithms from academic or industrial research. Testing, evaluating the AI/ML/DL models, benchmarking their quality, and publishing the models, data sets, and evaluations. Deploying the models in production by containerizing the models. Working with customers and internal employees to refine the quality of the models. Establishing continuous learning pipelines for models with online learning or transfer learning. Building and deploying containerized applications on the cloud or on-premise environments Required Qualifications BS or MS degree in computer science, computational. science/engineering, or related technical field (or equivalent experience). 3+ years of work-related experience in software development with good Python, Java, and/or C/C++ programming skills. Familiarity with containers, numeric libraries, modular software design. Hands-on expertise with traditional statistical machine learning techniques as well as deep-learning and natural language processing modeling. Expertise in supervised, unsupervised, and transfer learning techniques. Hands-on expertise in machine learning techniques and algorithms with a strong background in state-of-the-art DNN architectures (Transformers, CNN, R-CNN, RNN, BERT, GAN, autoencoders, etc.) and experience in developing or using major deep learning frameworks (e.g., PyTorch, Tensorflow, etc). Experience with solving and using machine learning for real-world problems. Preferred Experience and Skills Demonstrable experience in building, programming, and integrating software and hardware for autonomous or robotic systems. Proven experience producing computationally efficient software to meet real-time requirements. Background with container platforms such as Kubernetes. Strong analytical skills with a bias for action. Strong time-management and organization skills to thrive in a fast-paced, dynamic environment. Solid written and oral communications skills. Good teamwork and interpersonal skills. Compensation For U.S. Based candidates: To ensure fairness and transparency, the starting base salary range for this role for candidates in the U.S. are listed below, varying based on location experience, skills, and qualifications. In addition to base salary, this role will also be offered equity and subsidized benefits (details available upon request). Benefits Competitive base salary and equity Medical, dental, and vision (subsidized cost) Health savings accounts (HSA), flexible spending accounts (FSA), and dependent care FSAs (DCFSA) Retirement plan options, including 401(k) and Roth 401(k) Unlimited paid time off (PTO) 14 paid company holidays per year #LI-SM2 #LI-Onsite   Compensation$154,560—$193,200 USD  You're a Great Fit if You're A go-getter with a growth mindset. You're intellectually curious, have strong business acumen, and actively seek opportunities to build relevant skills and knowledge  A detail-oriented problem-solver. You can independently gather information, solve problems efficiently, and deliver results with a "get-it-done" attitude  Thrive in a fast-paced environment. You're energized by an entrepreneurial spirit, capable of working quickly, and excited to contribute to a growing company A collaborative team player. You focus on business success and are motivated by team accomplishment vs personal agenda  Highly organized and results-driven. Strong prioritization skills and a dedicated work ethic are essential for you    Equal Opportunity Statement At Armada, we are committed to fostering a work environment where everyone is given equal opportunities to thrive. As an equal opportunity employer, we strictly prohibit discrimination or harassment based on race, color, gender, religion, sexual orientation, national origin, disability, genetic information, pregnancy, or any other characteristic protected by law. This policy applies to all employment decisions, including hiring, promotions, and compensation. Our hiring is guided by qualifications, merit, and the business needs at the time.   Unsolicited Resumes and Candidates Armada does not accept unsolicited resumes or candidate submissions from external agencies or recruiters. All candidates must apply directly through our careers page. Any resumes submitted by agencies without a prior signed agreement will be considered unsolicited and Armada will not be obligated to pay any fees.  

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About LorikeetLorikeet is the most powerful customer support AI for complex businesses — fintechs, healthtechs, marketplaces, and delivery services.We're building from the ground up on the premise that most support responses should be automated with transparent, customizable AI, and that support teams should spend their time managing automation and engaging with complex cases — not grinding through high volumes of simple tickets. Once teams are freed from reactive support, we want to help them tackle what's next: delivering personalized, concierge-level service to their customers.To pull this off, we're drawing on Jamie's experience as an early member of Google's generative AI team, Steve's experience building for operational teams at Stripe, and a broader team that's come from Stripe, Canva, Atlassian, Dropbox, and Dovetail.We're growing fast, have paying customers, real revenue, and a strong pipeline. We've raised over USD $50M from leading VCs and angels including QED, Blackbird, Square Peg, Claire Hughes Johnson (ex-Stripe COO), Cristina Cordova (Linear COO), Bob Van Winden (Stripe Head of Support), and Cos Nicolaescu (Brex CTO).Our global customers include the largest telehealth company in Australia, the largest bank for teens in the US, one of the largest NFT marketplaces by trading volume, one of the largest Web3 gaming companies — and a handful of other enterprise customers processing over 1 million support tickets a year. What's unique about this opportunityYou'll be part of our first engineering team in New York. We're opening our first US engineering office and hiring a small, senior team from the ground up. Whether you're a strong mid-senior engineer ready for more scope or a staff engineer looking to lead — this is a chance to shape what the team looks like, not just join it.Technical founders and an engineering-led culture. Everyone at Lorikeet owns working with our users and building a great product for them. Engineers take on challenging problems, define solutions, and ship them — end to end, increasingly through agent-assisted workflows.We build at the frontier. Coding agents are central to how we work — they're doing a meaningful share of our coding. That doesn't mean pushing a button and shipping whatever comes out. It means exercising strong engineering judgment: knowing how to prompt well, iterate fast, set up the right feedback loops, and catch what the agent missed before it hits production.On the technical cutting edge. With our users, we're defining what an AI-first SaaS product looks like. No one has figured out the UI/UX, capabilities, and data models of an AI-first company — it's white space for us to invent. The agent problems we're solving go beyond the cutting edge at the biggest research labs.Warm, mature, in-person, flexible culture. Low ego, high trust. No tolerance for talented jerks. We work together in our New York office Monday through Thursday. People on the team have young families, so we embrace working efficiently and flexibly to fit life outside of work.High pay, high expectations, high performance. We pay US market rates and aim to match the best. On top of competitive base salaries, we offer a potentially life-changing equity stake. Our team gets the same monthly investor updates we send to our backers — because they're investors and owners too.About the roleYou'll be building something that's genuinely innovating the world of customer support. Together we'll be defining what AI-first product development looks like in practice — the UI/UX, the capabilities, the data models. It's a wide open problem space.Day to day, you'll take ownership of hard problems from idea to production. That means working closely with coding agents as a core part of your workflow, building the tooling and feedback systems that make them effective, and bringing the engineering judgment to know when the output is ready to ship — and when it isn't. Senior engineers will own features end-to-end; staff-level candidates will have the opportunity to shape technical direction for the team.Our stack is TypeScript, React/Remix, PrismaORM, NestJS, and some Python. Knowledge of the stack is nice; we know good engineers pick things up fast.We'd love to talk if youHave meaningful experience shipping code at a startup or company with high engineering standardsAre excited to work with a top-calibre team on genuinely novel AI problemsAre comfortable working with coding agents as a core part of how you build — not just as autocomplete, but as a real development workflowAre looking for a career-defining opportunity: real scope, real ownership, and real upside at a fast-moving companyIf you're from an underrepresented background and don't tick every box, please reach out anyway! We value user obsession and eagerness to learn over traditional credentials.

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JOB DESCRIPTION: The Aircraft Simulation team turns frontier autonomy into mission-ready aircraft. We own the commit-to-flight pipeline—deterministic aircraft and mission simulation, HITL/SITL integration, CI/CD, and tooling for automated flight qualification testing. Our goal is simple: make AI fly—safely, reliably, and fast.   As a Senior Modeling & Simulation Engineer, you will be dedicated to Shield AI’s next-generation aircraft program, contributing to our modeling and simulation tooling pipeline. You’ll design, build, and scale novel aircraft subsystem models, develop infrastructure that enables automated testing for our XBAT product line, and perform verification and validation of simulation pipelines. You will also conduct system performance analysis to evaluate expected and actual flight and mission performance using simulation tools and publish results for consumption by customers.   What You'll Do Develop models and infrastructure for the integrated simulation pipeline in C++.  Design deterministic, high-performance simulation tools capable of faster-than-real-time execution for development, testing, and release.  Implement test scenarios and write unit, system, and regression tests.  Collaborate across autonomy, embedded, GNC, and test engineering to ensure the simulation mirrors real aircraft behavior and mission scenarios.  Contribute to platform-agnostic simulation tooling to accelerate future development efforts  Perform verification and validation (V&V) analysis activities on model tools.  Conduct system performance analysis and generate reports and visualizations.  Utilize best practices in C++, simulation architecture, and performance engineering.  Required Qualifications BS or MS in Computer Science, Aerospace, Robotics, or related field.  5+ years of experience in software development, with emphasis on modern C++ (C++17 or later) and performance optimization.  Strong understanding of rigid-body dynamics, kinematics, and basic flight and sensor mechanics.  Proven experience developing or integrating simulation systems for robotics, aerospace, or autonomous systems.  Ability to debug complex build and runtime environments (CMake, CPM, package management, logging, & profiling tools).  Experience with software testing tools (GTest, etc.)  Experience with model V&V.  Strong collaboration and communication skills across software, hardware, and systems disciplines.  Preferred Qualifications Grasp of real-time and deterministic software design, including multi-threading, synchronization, and memory management.  Experience with DevOps-integrated simulation workflows, including CI/CD and automated hardware testing environments.  Working knowledge of Python for data analysis, test automation, or simulation orchestration.  Familiarity with aircraft and flight physics modeling.  105,000 - 155,000 a year#LI-SM1

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About Augment Code Augment Code is the only AI coding assistant built for professional software engineers working in large, production‑grade codebases. Our Context  Engine understands your entire repo, enabling developers to stay in flow while writing, reviewing, and understanding code. Backed by top‑tier investors and trusted by engineering teams at leading tech companies, Augment Code is redefining how modern software is built. About the role We’re looking for an Applied AI Engineer to help bring cutting-edge AI capabilities into the hands of developers. This is a hands-on engineering role at the intersection of product, AI, and systems — focused on implementing and integrating LLM-powered features that enhance developer experience and productivity. You’ll collaborate with engineers, researchers, and designers to translate product needs into intuitive, reliable AI-powered experiences. You’ll also play a key role in shaping how AI is used across our stack — from prompt design to system integration — while staying up to date on emerging AI capabilities. Examples of what you could do: Implement and integrate AI functionality into key product features Craft and iterate on prompts to improve LLM reliability and usefulness Build AI-powered flows that feel intuitive and responsive to developers Evaluate and test AI outputs to ensure performance and accuracy Work alongside engineers to deliver robust, production-grade code Stay current with LLM tools, APIs, and best practices You will… Deliver reliable, high-quality AI-powered product experiences Translate product needs into technical AI implementations Tune and test prompts for real-world use cases and developer workflows Collaborate closely with engineers and researchers Contribute across frontend, backend, and integration layers Qualifications: Strong coding skills in one or more of: Python, Go, Node.js, JavaScript, TypeScript, React, or Java Experience with API integrations and service-oriented architectures Familiarity with prompt engineering for LLMs (e.g. OpenAI, Claude, Gemini) Ability to evaluate and optimize AI outputs for reliability and quality Strong problem-solving instincts and attention to detail Collaborative mindset and eagerness to learn Bonus Points: Experience building product features that incorporate LLMs Understanding of best practices for AI reliability and safety Background in frontend development or UX-oriented implementation Familiarity with cloud platforms (especially GCP) Basic understanding of LLM behavior, strengths, and limitations Perks & Benefits We invest in creating an environment where you can do your best work and enjoy showing up. Comprehensive medical, dental, and vision coverage Unlimited paid time off Mental health and family-forming support Commuter benefits, including pre-tax options and a monthly stipend Daily lunch, stocked kitchens, and regular in-office events Thoughtful office setups, plus workspace and tools stipends Onsite gym access and a pet-friendly HQ A collaborative, in-person culture built around connection and momentum   We will do everything we can within reason to make sure that your interview takes place in an environment that fairly and accurately assesses your skills. If you need assistance or accommodation, please contact your recruiter. Augment Code is proud to be an Equal Employment Opportunity employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. By applying for this job, the candidate acknowledges and agrees that any personal data contained in their application or supporting materials will be processed in accordance with Augment Code's Applicant Privacy Policy.Pay Transparency Notice: The actual base salary within the stated range will be based on a combination of factors such as an individual's skills, experience level, educational background, and other relevant job-related considerations. Annual Base Salary Range$225,000—$300,000 USD

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Why HarveyAt Harvey, we’re transforming how legal and professional services operate — not incrementally, but end-to-end. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.This is a rare chance to help build a generational company at a true inflection point. With 1000+ customers in 60+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.Our team is sharp, motivated, and deeply committed to the mission. We move fast, operate with intensity, and take real ownership of the problems we tackle — from early thinking to long-term outcomes. We stay close to our customers — from leadership to engineers — and work together to solve real problems with urgency and care. If you thrive in ambiguity, push for excellence, and want to help shape the future of work alongside others who raise the bar, we invite you to build with us.At Harvey, the future of professional services is being written today — and we’re just getting started.Role OverviewAs a Software Engineer, Agents, you'll build the systems that make our AI agents indispensable to legal professionals.You will design environments and actions for agentic professional work, make model selection decisions, manage context windows, create optimal tools, and develop evals that enable faster iteration loops to unlock new capabilities.We're looking for engineers and researchers who are immersed in the space, driven to ship impactful products, and are experienced in using practical evaluations to drive task completion quality and customer delight.Representative ProjectsSave weeks of effort on high pressure M&A deals by automating information requests and diligence checks across hundreds of thousands of files with retrieval and file editing agents.Dramatically speed up deal turnaround speed by improving the latency and quality of agents on applying a standard legal "playbook" to contracts.Ensure that our clients win their complex, data-hungry litigation cases by optimizing our multi-source retrieval agents.Enable board-ready PowerPoint generation by tuning the harness and libraries for coding agents.What You'll DoPartner with customers and PMs to understand legal workflows, design practical evaluations that capture what “excellent” means, and ship agents that get the job done.Optimize agent performance through prompt engineering, model selection, tool design, skill writing, context window management, and eval harness development.Work with our model infra team to design and implement infrastructure for low-latency agent execution, including caching strategies, parallel tool calls, or subagent patterns.Improve our observability and instrumentation to profile agent behavior, identify bottlenecks, and drive optimization decisions.Stay current on new developments in agentic systems and bring those learnings back to the products we build.What You HavePassion for building effective domain-specific agents.Iterative mindset: you develop proof of concepts, make decisions quickly, and ship v0s.Comfortable with when and how to use evaluations to drive quality.Humble and adaptable about code and frameworks. We expect you to drive adoption of new best practices as they develop.3+ years (post-BS/MS) of software engineering experience. We are hiring for this role across Mid, Senior, and Staff levels.Proficiency in Python and experience working with LLM APIs and agent frameworks.Experience with shipping user-facing products, either on the backend or full-stack.Compensation Range$165,000 - $312,000 USDDepending on your location, an Applicant Privacy Notice may apply to you. You can find all of our Applicant Privacy Notices [here].#LI-BB1Harvey is an equal opportunity employer and does not discriminate on the basis of race, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition, or any other basis protected by law.We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made by emailing accommodations@harvey.ai

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V7At V7, we’re building AI platforms that help humans do their best work, at incredible scale and speed. Our mission is to turn human knowledge into trustworthy AI, making complex tasks faster, smarter, and more accurate. We’re growing fast, backed by leading investors and AI pioneers (including the minds behind Transformers and Gemini). The productV7 Go provides finance and teams with a toolkit for deploying and building custom no-code AI agents. We take multi-modal data and deliver verifiable outputs with transparent AI logic to ensure accuracy and compliance.Most AI agents still act like black boxes. They wander off-task, miss critical context, and make decisions you can’t verify. Go Agents are designed differently: predictable, transparent, and auditable at every step.V7 Go supports the latest models, such as GPT, Claude, and Gemini, for the best accuracy and performance.⁠⁠⁠⁠ Watch the V7 Go keynote to see what we’re building.The team you’ll be joining and the impact you’ll haveYou'll join our go-to-market team as our second Solutions Engineer in New York (the team is six people), sitting at the intersection of sales and product in a company processing tens of millions of documents for customers across finance, insurance, and real estate.V7 Go 4x-ed revenue last year, with 160%+ upsell into accounts. You'll help accelerate that trajectory by making sure every customer gets real value.We run a lean, high-trust team where you'll work directly with AEs, engineers, and product to close complex deals and turn new logos into long-term champions.Your work directly shapes how enterprises experience agentic AI for the first time and how quickly they believe in it.What you’ll be doing from day oneRun technical discovery, design solutions, and lead POCs alongside Account Executives to close deals, then own onboarding to get customers to first value fast.Build and implement workflows within V7 Go; combining prompt engineering, data pipelines, and integrations to solve real customer problems across document processing and more.Act as the primary technical contact for accounts, handling complex challenges and spotting expansion opportunities as customers scale.Juggle up to 10 concurrent projects while feeding customer insights back to product and engineering.Who you areYou are a prototyper at heart with a gift of talking to customers, building relationships, and solving technical problems with repeatability.You have experience in delivering Large Language Model projects with customers, including LLM API integration, up-to-speed knowledge of foundation models, solutions design/architecture, integrating different cloud providers, prompt engineering, and/or measuring AI accuracy.You love coding with Python.You can develop and articulate an AI solution vision to technical and business stakeholders, with customers and partners to match the value proposition to business needs.V7 champions equality and inclusion because diverse teams build better products. Don't check every box? Apply anyway — we value what makes you unique and will support you through the process, just let our Talent team know how they can help.

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About CartesiaOur mission is to build the next generation of AI: ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device.We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences.We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI.About The RoleData is the lifeblood of our models, and we are looking for a TLM, Data Infrastructure to own the strategy and execution for all data at Cartesia. This is a critical leadership role, where you will be responsible for building and managing the datasets that power our cutting-edge research. You will lead a talented team of data engineers and specialists to acquire, process, and curate massive multimodal datasets. Your vision will directly shape the capabilities and quality of our foundational models.What you’ll doDefine Cartesia’s overall multi-modal data strategy across pre-training and post-training, including human, synthetic, and web-scale data sources.Lead, manage, and mentor a team.Design and oversee the construction of robust, scalable data pipelines for text, audio, and video.Establish and enforce rigorous standards for data quality across the organization.Deeply understand how data affects model capability and proactively identify and source novel datasets.Manage relationships and budgets with external data vendors and partners.What we’re looking forTechnical expertise in large-scale data engineering.Familiarity with building datasets for and evaluating generative models.Leadership skills to grow and guide a high-impact data team.Our Culture🏢 We’re an in-person team based out of San Francisco. We love being in the office, hanging out together, and learning from each other every day.🚢 We ship fast. All of our work is novel and cutting edge, and execution speed is paramount. We have a high bar, and we don’t sacrifice quality or design along the way.🤝 We support each other. We have an open & inclusive culture that’s focused on giving everyone the resources they need to succeed.

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As a Software Engineer and member of the Platform Stability team, you will help build, fine-tune, and maintain a novel AI-powered tool for diagnosing technical issues and identifying root causes. You will collaborate cross-functionally to gather requirements, develop AI/ML and analytical models, and drive data-driven insights — all as part of a high-performing team.In this role, you will: Design and implement agentic AI systems with structured interfaces, reasoning loops, and robust error handling Build and maintain data pipelines, scheduled workflows, and benchmarking infrastructure Develop evaluation and scoring systems to measure and continuously improve model output quality Integrate the platform with internal and external services, including ticketing, messaging, storage, and observability Collaborate with cross-functional teams to translate business requirements into technical AI solutions Architect and maintain production-grade AI solutions with focus on scalability, reliability, and performance Qualifications BS in relevant engineering discipline and 4+ years of relevant work experience SW development, Strong Python with applications in AL/ML Familiarity with AI agents and their applications, including prompt design, tool calling, context management, and evaluation Experience or strong interest in Data Science and Engineering Experience or strong interest in creating Analytical or AI/ML-based models for real-world problems Strong problem-solving skills, especially in simplifying and modelling real-world problems Bonus Qualifications Familiarity with major LLM providers (OpenAI, Anthropic, Google, Meta, etc.) and understanding of their trade-offs in terms of performance, cost, latency, and capabilities Experience integrating AI capabilities into applications or eagerness to learn application development Full-stack development experience with both backend and frontend technologies 184,000 - 231,000 a yearBase Salary Range   There are three major components to compensation for this position: salary, Amazon Restricted Stock Units (RSUs), and Zoox Stock Appreciation Rights. A sign-on bonus may be offered as part of the compensation package. The listed range applies only to the base salary. Compensation will vary based on geographic location and level. Leveling, as well as positioning within a level, is determined by a range of factors, including, but not limited to, a candidate's relevant years of experience, domain knowledge, and interview performance. The salary range listed in this posting is representative of the range of levels Zoox is considering for this position.   Zoox also offers a comprehensive package of benefits, including paid time off (e.g. sick leave, vacation, bereavement), unpaid time off, Zoox Stock Appreciation Rights, Amazon RSUs, health insurance, long-term care insurance, long-term and short-term disability insurance, and life insurance.About ZooxZoox is developing the first ground-up, fully autonomous vehicle fleet and the supporting ecosystem required to bring this technology to market. Sitting at the intersection of robotics, machine learning, and design, Zoox aims to provide the next generation of mobility-as-a-service in urban environments. We’re looking for top talent that shares our passion and wants to be part of a fast-moving and highly execution-oriented team. Follow us on LinkedIn AccommodationsIf you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter. A Final Note:You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.