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About us:Articul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform combines domain-specific models, autonomous agentic reasoning through ModelMesh(TM), reliable model evaluation through LLM-IQ(TM), and multimodal understanding to serve regulated industries including energy, semiconductor, finance, aerospace, and supply chain. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand.Job Description:Articul8 AI is seeking a Principal Research Scientist to define how we build, evaluate, and scale domain-specific models as a durable source of competitive advantage. You will lead research across the full model development lifecycle: domain data strategy, continued pre-training, supervised fine-tuning, post-training, evaluation methodology, and the strategic decisions that determine where Articul8 can create and sustain model superiority in the market.Responsibilities:Set company-level technical direction for domain-specific model strategy — define how Articul8 builds, evaluates, scales, and sustains model superiority across continued pre-training, fine-tuning, post-training, and release quality standards, leveraging massively parallel agentic AI systems to compress strategic exploration cycles from months to daysArchitect the agentic model development paradigm for the organization — design the agent-orchestrated research infrastructure (experiment orchestration, data pipeline automation, continuous evaluation, competitive benchmarking) that enables every researcher at Articul8 to operate at a fundamentally higher level of depth, breadth, and velocity than would be possible aloneGo deep: push the frontier of domain-specific model science — lead research on model adaptation methodology, data curation strategies, post-training methods (preference optimization, reward modeling, reasoning improvement, alignment), and training dynamics, deploying fleets of agentic systems to run exhaustive ablation studies, mixture experiments, and failure analyses in parallelGo broad: shape model strategy across all of Articul8's domains and verticals — define how the company identifies, prioritizes, and enters new model domains based on technical feasibility, customer value, and strategic differentiation, using agent-driven competitive intelligence and market analysis to scan the landscape continuouslyDefine evaluation strategy as an agentic discipline — establish benchmark design, expert-grounded assessment, model failure analysis, and robustness standards, building always-on agentic evaluation harnesses that compare Articul8 models against leading open and closed alternatives and translate findings into concrete investment decisions in real timeLead cross-cutting research initiatives that multiply organizational capability — ensure advances in data perception, retrieval, post-training, and runtime orchestration strengthen the model layer, orchestrating parallel agent-driven research tracks across pillars so breakthroughs in one area compound across the platformInfluence platform-level decisions — shape model lifecycle management, portfolio strategy, release criteria, and integration architecture, ensuring the platform is designed for humans and agentic systems to co-evolve and amplify each otherMentor senior researchers and raise the ceiling on human potential — coach Staff and Senior researchers on designing agent-augmented research programs, raise the bar on technical judgment and experimental rigor, and shape hiring for researchers who are driven to redefine what's possibleMaintain hands-on research impact at the highest level — sustain a meaningful personal research contribution through technical work, publications, patents, and externally visible output, modeling what it means to be a world-class researcher who uses massively parallel agentic systems to achieve what was previously impossibleRequired Qualifications:Education: PhD or MSc in Computer Science, Machine Learning, NLP, or a related field.Experience: 10+ years in AI/ML research with an exceptional track record of impact — models or systems you built are in production and measurably changed outcomes. 4+ years developing LLM-based systems.Model lifecycle mastery: Deep hands-on experience across the full model development lifecycle — continued pretraining, supervised fine-tuning, post-training alignment, and production evaluation. You've made the hard calls about when a model is ready to ship and when it isn't.Evaluation rigor: You have designed evaluation methodology that goes beyond leaderboard metrics — domain-expert grounded assessment, systematic error analysis, robustness under distribution shift, and readiness criteria for high-stakes deployment.Training at scale: Direct experience training or adapting models on large GPU clusters using distributed frameworks (DeepSpeed, FSDP, Megatron-LM). You understand the interplay between data mixture, training compute, and model quality at a level that informs strategic decisions.Software engineering: Proficient in Python and PyTorch. You still write code, review code, and go deep when the problem demands it.Strategic leadership: You have shaped research direction at the organizational level — defining what bets to make, what to stop, and how to allocate research investment across competing priorities. People follow your direction because your judgment has been proven right.Preferred Qualifications:Experience building domain-specialized models that outperform general-purpose alternatives on specific, measurable tasks — not just fine-tuned checkpoints, but models with genuine domain understanding.Hands-on experience with post-training methods (RLHF, DPO, reward modeling, constitutional approaches) applied to real alignment problems, not just benchmark reproduction.Deep experience in data curation for model development — deduplication, mixture design, quality scoring — where your data decisions measurably changed model outcomes.Track record of designing evaluation frameworks for enterprise or regulated-industry use cases where a wrong answer has real consequences.Publication record at top-tier venues with evidence of sustained research leadership and influence on the field.Experience taking model research from prototype to production in a commercial setting where customers depend on the output.Domain expertise in one or more of: energy, semiconductor, finance, aerospace, or supply chain — you understand the data, the workflows, and why off-the-shelf models fail.Professional Attributes (Code42):Practice Humility: You lead with questions, not answers. You actively seek evidence that contradicts your strategy and revise publicly when warranted. You build an environment where senior researchers feel safe challenging your direction — because that's how the best decisions get made.Bias for Outcomes: You measure your impact by whether Articul8's models win in the market, not by the elegance of the research agenda. You make the hard calls about what to stop, what to double down on, and what to defer — and you own the results.Care Deeply: You treat the researchers you mentor as whole people, not output functions. You care about the quality of every model that ships under Articul8's name and intervene personally when standards are at risk. You build systems of feedback and recognition that make excellence visible.Dare to Do the Impossible & Embrace Scarcity: You define research bets that could change Articul8's competitive position for years. You don't let current scale limit the ambition of the model strategy. When resources are tight, you find the highest-leverage experiments and execute them with precision.Build a Better World: You ensure Articul8's model strategy serves not just business value but the industries and people who depend on these models for critical decisions. You hold the organization accountable for building AI that is trustworthy, auditable, and genuinely useful — because that's the only kind worth building.

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About us:Articul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform — combining domain-specific models, autonomous agentic reasoning (ModelMesh™), reliable model evaluation (LLM-IQ™), and multimodal understanding — serves regulated industries such energy, semiconductor, finance, aerospace, supply chain, and more. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand.Job Description:Articul8 AI is seeking an Applied AI Researcher to advance our domain-specific GenAI platform. You will design and run experiments, build training and evaluation pipelines, and ship research into production. This role spans model training, reinforcement learning, multimodal understanding, and knowledge representation.Responsibilities:Architect and orchestrate massively parallel AI research workflows — design experiments that leverage fleets of agentic AI systems to explore hypothesis spaces, hyperparameter landscapes, and architectural variations at a scale and speed no single researcher could achieve aloneDesign, train, and iterate on models across the full GenAI stack — LLMs, VLMs, embedding models, rerankers, and reward models — using agentic pipelines that autonomously manage data preprocessing, training runs, evaluation sweeps, and result synthesisGo deep: push the frontier of domain-specific AI — conduct rigorous, first-principles research into model architectures, training dynamics, reinforcement learning, and knowledge representation, using AI agents to accelerate literature review, ablation studies, and mathematical analysisGo broad: span disciplines and modalities — amplify your expertise across NLP, computer vision, multimodal understanding, agentic reasoning, and domain science by delegating exploration, prototyping, and benchmarking to parallel agent systems so you can synthesize insights across fields simultaneouslyBuild agentic research infrastructure — develop and contribute to shared tooling, libraries, and platforms that enable every researcher on the team to orchestrate autonomous experiment pipelines, data processing workflows, and evaluation harnesses at scaleShip research into production at velocity — collaborate with engineering, product, and domain experts to integrate breakthroughs into the platform rapidly, using agentic CI/CD and automated integration testing to compress the research-to-deployment cycleAmplify collective intelligence — document findings, publish at top-tier venues, and build internal knowledge systems that agentic tools can index and reason over — turning every insight into a force multiplier for the entire teamContinuously raise the ceiling on human potential — proactively identify bottlenecks in your own workflow and the team's, then design or adopt efficient, scalable solutions that eliminate them — treating your own augmentation as a core research outputRequired Qualifications:Education: PhD in Computer Science, Machine Learning, or a related field; or MSc with 4+ years of post-graduation research experience.Model development: You have trained or fine-tuned at least one neural model end-to-end — data preparation through evaluation. You understand why your model converges or doesn't, not just how to launch a training run.Technical foundations: Strong working knowledge of probability, optimization, and linear algebra applied to at least one of: NLP, computer vision, reinforcement learning, or information retrieval. You can derive the math behind the methods you use.Infrastructure: Experience building training or evaluation pipelines that handle real data — preprocessing, distributed computation, experiment tracking, and reproducibility.Software engineering: Production-quality Python. You write code others can read, test, and extend. Fluent with Git and collaborative development workflows.Preferred Qualifications:Experience with distributed training frameworks (PyTorch DDP, DeepSpeed, FSDP) — you understand gradient synchronization and can debug multi-GPU failures.Published at NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, or equivalent. Quality of contribution matters more than count.Hands-on experience with post-training methods (RLHF, DPO, reward modeling) — beyond reading papers.Practical cloud infrastructure experience (AWS, GCP, or Azure) for ML workloads — you can provision resources, manage jobs, and troubleshoot training failures.Professional Attributes (Code42):Practice Humility: You ask questions even when you think you know the answer. You seek feedback early, learn from anyone regardless of title, and treat every experiment — especially the failures — as data.Bias for Outcomes: You measure your work by what changed, not what you tried. You ship results, not slide decks. When a deadline is real, you find a way.Care Deeply: You treat every problem as yours to solve. You review your own work with the rigor you'd want from a reviewer. You help teammates without being asked.Dare to Do the Impossible & Embrace Scarcity: You set goals that make you uncomfortable. When told something can't be done, you find a way or a better question. Constraints sharpen your thinking, not slow it down.Build a Better World: You believe AI should make things meaningfully better for real people. You hold yourself accountable not just for whether your model works, but for what it does in the world.

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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities.  This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who you are BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.   What we need Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes. Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly. Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR. Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.   What you will learn How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows. New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits. Best practices for deploying, validating, and monitoring ML models in production CAD environments. How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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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.8+ 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$231,000 - $340,000 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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Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities.Tenstorrent is seeking an Physical Design Engineer to lead  cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities.  This role is hybrid, based out of Santa Clara, CA or Austin, TX or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting.   Who you are BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independently.   What we need Lead and contribute to cross-functional efforts solving complex physical design challenges across IPs, projects, and advanced technology nodes. Develop and enhance RTL-to-GDS methodologies, including floorplanning, synthesis, P&R, STA, signoff, and assembly. Architect and deploy AI/ML-driven solutions in production flows to improve engineering efficiency, turnaround time, and QoR. Optimize EDA tools and custom CAD flows using data-driven and ML-based techniques, in close collaboration with verification, extraction, timing, DFT, and EDA vendors.   What you will learn How to scale AI/ML-driven methodologies across diverse products and advanced technology nodes in real production flows. New ways to blend classical EDA algorithms with modern ML techniques to push PPA and runtime limits. Best practices for deploying, validating, and monitoring ML models in production CAD environments. How to influence next-generation ML-enabled EDA tools and collaborate deeply with cross-functional teams (PV, extraction, timing, DFT).   Compensation for all engineers at Tenstorrent ranges from $100k - $500k including base and variable compensation targets. Experience, skills, education, background and location all impact the actual offer made. Tenstorrent offers a highly competitive compensation package and benefits, and we are an equal opportunity employer. This position requires access to technology that requires a U.S. export license for persons whose most recent country of citizenship or permanent residence is a U.S. EAR Country Groups D:1, E1, or E2 country. This offer of employment is contingent upon the applicant being eligible to access U.S. export-controlled technology.  Due to U.S. export laws, including those codified in the U.S. Export Administration Regulations (EAR), the Company is required to ensure compliance with these laws when transferring technology to nationals of certain countries (such as EAR Country Groups D:1, E1, and E2).   These requirements apply to persons located in the U.S. and all countries outside the U.S.  As the position offered will have direct and/or indirect access to information, systems, or technologies subject to these laws, the offer may be contingent upon your citizenship/permanent residency status or ability to obtain prior license approval from the U.S. Commerce Department or applicable federal agency.  If employment is not possible due to U.S. export laws, any offer of employment will be rescinded.

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Who We Are PathAI's mission is to improve patient outcomes with AI-powered pathology. Our platform promises substantial improvements to the accuracy of diagnosis and the efficacy of treatment of diseases like cancer, leveraging modern approaches in machine learning and artificial intelligence. We have a track record of success in deploying AI algorithms for histopathology in translational research, pathology labs and clinical trials.  Rigorous science and careful analysis is critical to the success of everything we do. Our team, composed of diverse employees with a wide range of backgrounds and experiences, is passionate about solving challenging problems and making a huge impact on patient outcomes. Where You Fit  As the Associate Director, MLOps Lead, you will lead the team responsible for the backbone of our AI/ML Stack: the infrastructure that bridges ML research and massive-scale production. Your primary directive is to evolve our stack to meet the next scale of needs in large scale ML training & inference workloads.   You’re someone who enjoys designing and building for reliability, relishes collaboration and technical challenges, and takes pride in making things better – without taking yourself too seriously. Our technical space is broad: high-scale AI training & inference workloads, cloud infrastructure, Kubernetes, observability, distributed systems, and a bit of everything in between. What You’ll Do This role is critical for driving the scalability and efficiency of our Machine Learning Operations platform with high-impact & high growth strategic initiatives.  Vision and Roadmap: Develop and execute the long term vision & roadmap for MLOPs team to support ML development and deployment needs across the business units. Successfully manage the tension between short-term tactical deliveries and long-term architectural transformation for future growth.  Team Management: Lead and mentor a team of 6-7+ high-performing engineers. Strategically allocate resources to manage support for existing services while executing key strategic initiatives. Cross-Functional Collaboration: Partner with leaders across machine learning, data science, product engineering, and infrastructure to proactively identify pain points, address bottlenecks, and facilitate the deployment of new solutions. Foundation Model Readiness: Architect the compute and storage pipelines required for ML Engineers to manage millions of slides and complex derived artifacts without data fragmentation or synchronization latency. Inference Modernization: Modernize the AI Product inference stack to support 5-10x growth of AI runs across global deployments. System Observability: Collaborate with Site Reliability Engineering (SRE) to establish comprehensive metrics covering compute under-utilization, network bottlenecks, and granular cost and turn-around-time attribution. Technology Refresh: Conduct "Build vs. Buy" assessments, leading "Stack Refresh" audits to benchmark our proprietary tools against best-in-class commercial and open-source alternatives to meet our future needs. What You Bring To be successful in this role with us, you'll at least need: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience). 2-3+ years of experience managing engineering team(s), with a focus on building production-grade frameworks for MLOps or ML Infrastructure. Deep technical expertise with ML workloads on kubernetes, cloud computing platforms (AWS/GCP/Azure), workflow orchestration (Airflow, Kubeflow, or proprietary equivalents) and DevOps principles and infrastructure-as-code (Helm, Terraform). Proven experience managing petabyte-scale datasets and high-throughput production inference pipelines. Strong software engineering skills in complex, multi-language systems and experience with scalable service architecture. Use of AI assistants (e.g. CoPilot, Cursor, Claude) across platform development lifecycle. It Would Be Great If You Also Have Exposure to ML frameworks like PyTorch or Scikit-learn. Experience with large-scale data processing frameworks (e.g. Spark, Hive, Databricks, Amazon EMR) Expertise in MLOps principles, including model lifecycle management, feature stores, model monitoring, and CI/CD for ML. Familiarity with security and compliance best practices in ML systems. We Want To Hear From You At PathAI, we are looking for individuals who are team players, are willing to do the work no matter how big or small it may be, and who are passionate about everything they do. If this sounds like you, even if you may not match the job description to a tee, we encourage you to apply. You could be exactly what we're looking for.  PathAI is an equal opportunity employer, dedicated to creating a workplace that is free of harassment and discrimination. We base our employment decisions on business needs, job requirements, and qualifications — that's all. We do not discriminate based on race, gender, religion, health, personal beliefs, age, family or parental status, or any other status. We don't tolerate any kind of discrimination or bias, and we are looking for teammates who feel the same way. The cash compensation outlined below includes base salary or hourly wage and on-target commission for employees in eligible roles. The summary below indicates if an employee in this position is eligible for annual bonus, overtime pay and equity awards. Individual compensation packages are tailored based on skills, experience, qualifications, and other job-related factors.  Annual Pay Range: AD, MLOps: $181,500 - $278,300 Not Overtime Eligible Eligible for Equity

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About us:Articul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform — combining domain-specific models, autonomous agentic reasoning (ModelMesh™), reliable model evaluation (LLM-IQ™), and multimodal understanding — serves regulated industries such energy, semiconductor, finance, aerospace, supply chain, and more. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand.Job Description:Articul8 AI is seeking an Applied AI Researcher to advance our domain-specific GenAI platform. You will design and run experiments, build training and evaluation pipelines, and ship research into production. This role spans model training, reinforcement learning, multimodal understanding, and knowledge representation.Responsibilities:Architect and orchestrate massively parallel AI research workflows — design experiments that leverage fleets of agentic AI systems to explore hypothesis spaces, hyperparameter landscapes, and architectural variations at a scale and speed no single researcher could achieve aloneDesign, train, and iterate on models across the full GenAI stack — LLMs, VLMs, embedding models, rerankers, and reward models — using agentic pipelines that autonomously manage data preprocessing, training runs, evaluation sweeps, and result synthesisGo deep: push the frontier of domain-specific AI — conduct rigorous, first-principles research into model architectures, training dynamics, reinforcement learning, and knowledge representation, using AI agents to accelerate literature review, ablation studies, and mathematical analysisGo broad: span disciplines and modalities — amplify your expertise across NLP, computer vision, multimodal understanding, agentic reasoning, and domain science by delegating exploration, prototyping, and benchmarking to parallel agent systems so you can synthesize insights across fields simultaneouslyBuild agentic research infrastructure — develop and contribute to shared tooling, libraries, and platforms that enable every researcher on the team to orchestrate autonomous experiment pipelines, data processing workflows, and evaluation harnesses at scaleShip research into production at velocity — collaborate with engineering, product, and domain experts to integrate breakthroughs into the platform rapidly, using agentic CI/CD and automated integration testing to compress the research-to-deployment cycleAmplify collective intelligence — document findings, publish at top-tier venues, and build internal knowledge systems that agentic tools can index and reason over — turning every insight into a force multiplier for the entire teamContinuously raise the ceiling on human potential — proactively identify bottlenecks in your own workflow and the team's, then design or adopt efficient, scalable solutions that eliminate them — treating your own augmentation as a core research outputRequired Qualifications:Education: PhD in Computer Science, Machine Learning, or a related field; or MSc with 4+ years of post-graduation research experience.Model development: You have trained or fine-tuned at least one neural model end-to-end — data preparation through evaluation. You understand why your model converges or doesn't, not just how to launch a training run.Technical foundations: Strong working knowledge of probability, optimization, and linear algebra applied to at least one of: NLP, computer vision, reinforcement learning, or information retrieval. You can derive the math behind the methods you use.Infrastructure: Experience building training or evaluation pipelines that handle real data — preprocessing, distributed computation, experiment tracking, and reproducibility.Software engineering: Production-quality Python. You write code others can read, test, and extend. Fluent with Git and collaborative development workflows.Preferred Qualifications:Experience with distributed training frameworks (PyTorch DDP, DeepSpeed, FSDP) — you understand gradient synchronization and can debug multi-GPU failures.Published at NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, or equivalent. Quality of contribution matters more than count.Hands-on experience with post-training methods (RLHF, DPO, reward modeling) — beyond reading papers.Practical cloud infrastructure experience (AWS, GCP, or Azure) for ML workloads — you can provision resources, manage jobs, and troubleshoot training failures.Professional Attributes (Code42):Practice Humility: You ask questions even when you think you know the answer. You seek feedback early, learn from anyone regardless of title, and treat every experiment — especially the failures — as data.Bias for Outcomes: You measure your work by what changed, not what you tried. You ship results, not slide decks. When a deadline is real, you find a way.Care Deeply: You treat every problem as yours to solve. You review your own work with the rigor you'd want from a reviewer. You help teammates without being asked.Dare to Do the Impossible & Embrace Scarcity: You set goals that make you uncomfortable. When told something can't be done, you find a way or a better question. Constraints sharpen your thinking, not slow it down.Build a Better World: You believe AI should make things meaningfully better for real people. You hold yourself accountable not just for whether your model works, but for what it does in the world.

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About Us:Articul8 was born from a simple belief: GenAI should work for the enterprise, not the other way around. Our platform — combining domain-specific models, autonomous agentic reasoning (ModelMesh™), reliable model evaluation (LLM-IQ™), and multimodal understanding — serves regulated industries such energy, semiconductor, finance, aerospace, supply chain, and more. Trusted by Fortune 500 enterprises, we bring together research, engineering, product, and domain expertise to deliver AI that meets the accuracy, explainability, and auditability standards that high-stakes environments demand.Job Description:Articul8 AI is seeking a Senior Applied AI Researcher to solve open research problems across our domain-specific GenAI platform. You will own research projects end-to-end — from problem formulation through production deployment. This role spans model training, reinforcement learning, multimodal understanding, and knowledge representation — with deep expertise in at least one area.Responsibilities:Own and orchestrate end-to-end research programs using massively parallel agentic AI — from problem formulation through production deployment, designing agent-driven experiment campaigns that simultaneously explore model architectures, training regimes, data strategies, and evaluation criteria at a pace and breadth that redefines what a single researcher can accomplishGo deep: drive breakthrough domain-specific model quality — lead multi-stage training pipelines, domain adaptation, RL-based optimization (RLHF, DPO, reward modeling), and training dynamics analysis, using agentic systems to run exhaustive ablations, hyperparameter sweeps, and failure-mode investigations in parallelGo broad: span modalities, methods, and domains simultaneously — design and train multimodal systems (text, images, tables, charts, technical documents), knowledge graph pipelines, hybrid retrieval architectures, and structured reasoning systems, delegating exploration and prototyping across these fronts to parallel agent workflows so you can synthesize cross-cutting insights in real timeArchitect agentic data and training infrastructure — build agent-orchestrated pipelines for domain-specific data curation, quality filtering, preprocessing, and large-scale training that the entire research team can leverage to go fasterMentor AI Researchers in the agentic paradigm — coach team members on how to amplify their own depth and breadth by designing effective agent workflows, raising the ceiling on what every researcher can achieveCompress the research-to-production cycle — take prototypes to production-ready systems rapidly by leveraging agentic CI/CD, automated integration testing, and continuous evaluation harnesses, collaborating closely with engineering, product, and domain expertsBuild force-multiplying knowledge systems — document findings, publish at top-tier venues, and contribute to internal knowledge infrastructure that agentic tools can index and reason over, turning every breakthrough into compounding team-wide leverageModel the augmented researcher — continuously identify bottlenecks in your own and the team's workflows, then design or adopt efficient, scalable solutions that eliminate them — treating the maximization of human potential as a first-class research outputRequired Qualifications:Education: PhD or MSc in Computer Science, Machine Learning, or a related field.Experience: 5+ years as an AI/ML researcher with shipped research artifacts (models, systems, or tools in production), including 2+ years building LLM-based systems.Model training depth: You have run multi-stage training pipelines (pretraining, fine-tuning, post-training) and can diagnose training failures from loss curves, gradient norms, and evaluation metrics — not just restart the job.Technical specialization: Deep expertise in at least one of: domain-specific model adaptation, multimodal learning, reinforcement learning from human feedback, knowledge-grounded generation, or retrieval-augmented systems. You've published or shipped production work in your area.Distributed systems: Hands-on experience with distributed training at scale (DeepSpeed, FSDP, Megatron-LM, or equivalent). You understand data parallelism vs. model parallelism and know when each matters.Software engineering: Production-grade Python, clean abstractions, tested code. You build tools others depend on.Preferred Qualifications:Experience adapting models to specialized domains where standard benchmarks don't apply — you've had to define what "correct" means and build evaluation around it.Track record of taking a research prototype to a production system serving real users.Experience with knowledge graph construction, hybrid retrieval architectures, or structured reasoning systems in practice — not just in papers.Strong publication record with evidence of depth, not just breadth.Cloud-native ML infrastructure experience (Kubernetes, distributed job scheduling, GPU cluster management).Professional Attributes (Code42):Practice Humility: You stay open to being wrong — even on problems you've studied for years. You actively seek perspectives that challenge your assumptions and create space for junior researchers to teach you something new.Bias for Outcomes: You own the outcome end-to-end, from research question to production impact. You know the difference between interesting work and important work, and you choose the latter. Dates and scope are commitments, not suggestions.Care Deeply: You treat your team's problems as your own. You give honest, specific feedback because you care about the person's growth, not just the project. When something is broken, you fix it or flag it — you never walk past it.Dare to Do the Impossible & Embrace Scarcity: You pursue research directions others have written off. You use resource constraints as forcing functions for creative solutions, not excuses. Your ambition is calibrated to what the problem demands, not what feels safe.Build a Better World: You hold yourself to the standard that your work should make the enterprise smarter, not just the model better. You mentor others because raising the bar for the whole team is how you multiply impact.

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About Loop Loop is the data platform for the global supply chain. Logistics runs on messy, unstructured data—trapped in PDFs, emails, and legacy systems. We use AI to structure this chaos, creating a "source of truth" that automates payments and audits for the Fortune 100. We are building the financial nervous system for a $100 trillion physical economy. Our technology ensures freight moves efficiently and carriers get paid instantly. Backed by Founders Fund, Index Ventures and 8VC, we are scaling rapidly. We are looking for engineers ready to deploy production AI that powers the physical economy. About the New Grad Program Most AI stays in the browser. Ours moves atoms. You aren't just building features; you are building the autonomous brain for the Fortune 100’s global supply chain. This program is designed to compress 3 years of learning into 1 year by throwing you into the deep end of production AI systems on Day 1. Instead of sandboxed projects, you get to solve real problems and impact customers directly. This program demands intense investment, but by the end, you will perform as a strong entry-level engineer jumpstarting your career. The Schedule: Week 1 (Onboarding): Deep dive into tools and domain. You will ship code to production on Day 1 and fully grasp our dev loop by Friday. Months 1-3 (Velocity): You will deliver 3 entry-level projects with increasing ambiguity. By the end of Month 3, you are expected to operate as a fully independent engineer. Months 4-9 (The Rotation): You will rotate onto a different high-impact team to expand your surface area. Tracks include: Platform: AI infrastructure and Engineering Systems. Core Product: Audit, Billing, and Payments logic. Commercial: Revenue Activation and Forward Deployed Engineering. Special Projects: Partnering directly with the CEO/CTO and other execs Month 9+ (Graduation): You should demonstrate Mid-Level Engineer performance and will be considered for immediate promotion. About You We're not just looking for strong academic performers. We're looking for people who are genuinely driven to build things and go deep on hard problems. If the following resonates, you belong here: You go above and beyond. You have a repo, a side hustle, or a project you built just because you are curious. You’re self-directed and don't need an assignment to start coding. You have a bias towards action. You prefer to ship, break, fix, and apologize rather than wait for a committee decision. You are drawn to hard problems. You want problems that are more than one prompt away from a solution. You get absorbed in mastering your craft. Whether it’s climbing the Esports ladder, acing a math competition, winning a hackathon, or debugging a complex issue, you know what it feels like to lose track of time working on something you care about. Responsibilities Ship critical infrastructure. Manage real-world logistics and financial data for the largest enterprise in the world..  Own the why. Build deep context through customer calls, and understand the Loop’s value to our customers. You push back on requirements if you see a better, faster way to solve the customer’s problem. Full-stack proficiency. Work across system boundaries, from frontend UX to LLM agents, database schema and event infrastructures. Leverage AI tools to handle the 90% boilerplate, so you can focus the highest leverage 10%: quality, architecture, product taste. Raise the velocity bar. You will constantly optimize our dev loops, refactor legacy patterns, automate your own workflows and fix broken processes. Qualifications Graduating with a BS or higher in STEM fields; available to start full-time in 2026. Working in person in the SF or Chicago office 4 days a week. Proficiency with modern techstack. You can deliver a modern web app in hours not in days.. Unblocking yourself. You thrive in ambiguity. Despite the chaos, you deliver high quality products and business impact. AI Literate. You have strong intuition on how LLM works: where they excel and where they generate slop. You live and breathe AI native tools (Cursor, Codex, Claude Code etc.) Compensation $150,000 annual base pay for SF $125,000 annual base pay for Chicago Benefits & Perks Fully paid health insurance. 401k with matching. Unlimited PTO. Generous professional development budget. Commuter benefits. Wellness benefits Phone plan stipend #LI-LOOP

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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.8+ 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$231,000 - $340,000 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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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-Hybrid

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Lumana is on a mission to empower organizations by unlocking the value of their visual data — not just record the world, but to actually understand it and extract meaningful insights. Our AI video security platform delivers unmatched visibility and control, helping customers enhance security and safety, streamline operations, and respond instantly when it matters most.Founded in 2021, we are backed by tier-one Silicon Valley investors with deep team expertise in AI, computer vision, and machine learning. We are one of the fastest-growing video security companies and recently raised the largest Series A within our industry. We’ve built the most intelligent video security solution on the market — one that sees what matters, acts fast, and prevents what used to be inevitable.At Lumana, teams are small, dynamic, and trusted to lead. We think big, move fast, and execute like owners — because we are. Your impact here won’t be filtered. It will be visible, lasting, and real.Role DescriptionThe Senior Software Engineer, Edge Lumana's growing engineering organization and help build the software that runs on the core device layer behind our platform. This role sits within a small, highly impactful team responsible for a hybrid edge system that powers core functionality across video, security, networking, storage, and AI deployment in production environments. You'll work on a resource-conscious, distributed device architecture that spans multiple hardware targets and brings together technologies more commonly seen across both embedded and cloud systems. This is a strong fit for an engineer who enjoys meaningful ownership, thrives in a fast-moving startup environment, and is comfortable building reliable software for systems customers depend on every day.Location & TravelHybrid / Onsite Schedule: Based in Caesarea, with 2 days a week working from home. ResponsibilitiesContributing to the development of our core edge platform, designed to run across diverse hardware environments as part of a hybrid edge-cloud architectureDeveloping and integrating video management capabilities, including streaming, recording, and real-time AI processingDesigning and optimizing systems for low-latency, high-performance workloads at the edgeBuilding secure and efficient communication pipelines between edge devices and cloud systemsWorking closely with AI/ML engineers to deploy and optimize models on-deviceParticipating in code reviews, debugging, and performance tuning across the stackCollaborating with a talented team of engineers, AI experts, and leadership in a fast-moving environmentWe don’t do cookie-cutter. If you don’t check every box but you’ve got the grit, the drive, and the track record—especially in security or AI—we encourage you to apply.Requirements5+ years of experience in software engineering, with a focus on systems or performance-critical applicationsStrong experience with modern programming languages such as Go, Rust, or TypeScriptProven experience with multithreaded and concurrent programming (critical for this role)Solid understanding of Docker and containerizationExperience working with embedded systems or edge computing environmentsStrong understanding of networking and distributed systems fundamentalsExperience building or working with real-time systemsNice to HaveExperience with video streaming or video pipeline developmentFamiliarity with storage systems and data management at the edgeExperience integrating with cloud services (e.g., AWS S3, GCP, MQTT, Kafka)Exposure to deploying or optimizing AI/ML models on edge devicesBackground in security concepts (encryption, secure communication, zero trust architectures)Experience with hardware-aware optimization (CPU/GPU/accelerators)✍️ Lumana Hiring PhilosophyWe spend a lot of time building best-in-class products since we believe a highly differentiated product is easier to sell and support. We aim to provide both product & industry expertise whenever we interact with prospects and customers. We strongly believe that small teams with very talented people (and the right work environment) deliver much better performance than teams with large headcount. We hire and compensate accordingly. We value a strong sense of ownership, principled thinking over experience, and thoughtful communication.Our Interview ProcessWe keep it focused and respectful of your time—our typical process includes:A 30-minute conversation with our Talent Team to learn more about you and share what we're buildingA 60-minute interview with our CTO to dive into your background and experienceAt-Home Assignment (3 hour)A 90-minute technical session in office with our Team to dive into your assignment, systems thinking, and coding familiarityA 60-minute conversation with our CTO to dive into your assignment Curious who you’d be working with? Meet the Team → ✨ What We OfferWe believe great talent deserves great support. Here’s how we invest in you:Competitive Pay: A strong base salary that reflects your experience, impact, and market valueEquity & Upside: Own a piece of what you're building with meaningful equity in a fast-growing startupTools that Work for You: Get access to top-tier tech and a fully equipped workspace—both in-office and at homeHybrid Flexibility: Enjoy a balanced schedule with two remote workdays each week after ramp-upProduct Influence: Your voice matters—your hands-on feedback directly shapes our product roadmapFor Israel-Based EmployeesMonthly 10Biz allowance: 1,000 shekelTravel allowance: 500 shekelVacation: 14 days, with up to 21 days carry over; Sick pay from day 1Keren Hishtalmut (Study Fund) matchEquipment: Laptop provided, and ILS 700 reimbursable home office setup allowance used within first 6 monthsLumana is an equal opportunity employer‍We are committed to providing equal employment opportunities to all individuals regardless of race, color, ethnicity, religion, sex, gender identity, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis protected by law.Recruitment Fraud Alert: All Lumana hiring communications come from @lumana.ai — we never ask for payment or personal banking info.Recruiters & Agencies: Lumana does not accept unsolicited resumes from agencies without a signed agreement and will not pay related fees.

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About HandshakeHandshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.Why join Handshake now:Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feelWork hand-in-hand with world-class AI labs, Fortune 500 partners and the world’s top educational institutionsJoin a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among othersBuild a massive, fast-growing business with billions in revenueAbout the roleHandshake AI is at the frontier of applied AI — working with world-class labs and partners on genuinely hard problems around human data, evals, and AI systems. The engineering team here ships production solutions that matter: reliable, observable, and built to scale.As a Tech Lead Manager, you're first and foremost a builder. You'll set technical direction for a small team of engineers while staying deeply hands-on — writing production code, architecting systems, and driving work forward. This is a player-coach role, ideal for a senior engineer ready to take on their first or second management scope without leaving the craft behind.The best person for this role leads by example, builds trust through technical credibility, and creates structure without bureaucracy.Location: San Francisco, CA | 5 days/week in-officeWhat you'll doWrite production-quality code and architect systems that are reliable, observable, secure, and maintainable.Set technical direction for a small team — define the approach, unblock engineers, and raise the bar on quality.Manage and develop a team of 3–5 engineers: set expectations, have real feedback conversations, and help people grow.Own end-to-end delivery across multiple concurrent workstreams — triage, prioritize, and flag scope or capacity issues early.Design and build integrations, tooling, APIs, and internal systems in close collaboration with research, product, and operations teams.Identify patterns across workstreams and build reusable components that scale the team's output.Communicate clearly with technical and non-technical stakeholders alike — translate tradeoffs into decisions and keep the right people informed.Must haves6+ years of software engineering experience, with meaningful depth in backend, fullstack, or systems work.Experience as a tech lead or TLM — setting technical direction for a team, not just owning your own work.1–2 years managing a small team of engineers (3–6); comfortable with feedback, growth conversations, and performance.Must be someone who codes regularly and wants to keep coding — this is not a transition-to-management role.Experience working closely with non-engineering stakeholders (research, product, operations, or similar) — comfortable translating between technical and business context.Strong communication skills: clear under pressure, able to present options and recommendations to varied audiences.Sharp instincts on triage and prioritization across multiple concurrent workstreams.Nice to havesExperience with AI/ML systems or production reliability in AI-adjacent environments.Familiarity with distributed systems and backend architecture at scale.Experience building reusable platforms or internal tooling from bespoke solutions.Background working with or alongside research or operations-heavy organizations.Why join nowStay close to the craft while growing as a leader — this role is built for engineers who don't want to stop building.Work on genuinely hard problems at the frontier of applied AI with world-class labs and partners.Join early and help shape how the engineering org scales — your patterns become the playbook.Direct, visible impact on Handshake AI's most important technical work and strategic relationships.PerksHandshake delivers benefits that help you feel supported—and thrive at work and in life.The below benefits are for full-time US employees.🎯 Ownership: Equity in a fast-growing company💰 Financial Wellness: 401(k) match, competitive compensation, financial coaching🍼 Family Support: Paid parental leave, fertility benefits, parental coaching💝 Wellbeing: Medical, dental, and vision, mental health support, $500 wellness stipend📚 Growth: $2,000 learning stipend, ongoing development💻 Remote & Office: Internet, commuting, and free lunch/gym in our SF office🏝 Time Off: Flexible PTO, 15 holidays + 2 flex days🤝 Connection: Team outings & referral bonusesExplore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.

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Full Stack AI Engineer (.NET) RYZ Labs is looking for a Full Stack AI Engineer to help build and improve intelligent features across our client’s platform. This role involves working across both frontend and backend systems, with a focus on integrating AI capabilities into user-facing and internal tools. You’ll collaborate with product, engineering, and data teams to develop scalable solutions that enhance user experience, automate workflows, and improve system efficiency.   About RYZ Labs: RYZ Labs is a startup studio founded in 2021 by two lifelong entrepreneurs. Our teams are remote and distributed across the US and LatAm, working with cutting-edge technologies to build scalable, impactful products. At RYZ, you’ll work with autonomy and ownership in a fast-paced environment, contributing to meaningful projects while continuing to grow alongside a strong team.Responsibilities: Develop and maintain full stack applications using modern frontend frameworks (React or similar) and .NET-based backend services Build and integrate AI-powered features (e.g., automation, summarization, recommendations) into existing workflows Design and consume REST APIs and support backend services in .NET Collaborate with cross-functional teams to identify opportunities for automation and AI-driven improvements Work with structured and unstructured data to support AI/ML use cases Contribute to improving system performance, scalability, and reliability Support basic monitoring and troubleshooting of production systems Basic Qualifications: 3–5+ years of experience as a Full Stack Engineer or Software Engineer Strong experience with .NET (C#) for backend development Experience with JavaScript/TypeScript and a modern frontend framework (React preferred) Familiarity with building and consuming REST APIs Basic experience working with AI/ML concepts or tools (e.g., APIs, LLMs, or automation workflows) Experience working with cloud platforms (AWS, Azure, or GCP) is a plus Good understanding of software development best practices Nice to Have: Exposure to AI tools such as OpenAI, embeddings, or prompt-based systems Experience with SQL or NoSQL databases Familiarity with CI/CD pipelines Interest in automation and improving operational workflows

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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-Hybrid

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Who We AreCognition is an applied AI lab building end-to-end software agents. We are behind Devin, the first AI software engineer, and Windsurf, an AI-native IDE. Our vision is AI that works alongside engineers as a genuine teammate, not a tool.We are a small, talent-dense team of competitive programmers, former founders, and researchers from Scale AI, Palantir, Cursor, Google DeepMind, and others.Role MissionSoftware Engineers at Cognition are not feature builders. You will be working on some of the hardest open problems in applied AI: how do you build an agent that can reason across thousands of lines of code, spawn and coordinate subagents, use tools reliably across ambiguous long-horizon tasks, and do all of this in a way that a real engineer would trust? You will ship systems that go directly into Devin and Windsurf, two products that millions of developers use to write, debug, and ship code. This is a role for engineers who want to be close to the frontier, who can move fast without cutting corners, and who believe the next 5 years of software engineering will look fundamentally different from the last 5.What You'll AccomplishBuild core agent infrastructure: Design and ship the systems that power Devin's long-horizon task execution: tool use, context management, multi-step planning, subagent orchestration, and sandboxed code execution environments.Improve Windsurf as an AI-native IDE: Contribute to editor intelligence, agent-in-the-loop workflows, real-time code understanding, and the developer experience that makes Windsurf different from every other IDE.Close the loop between models and products: Work directly with researchers to translate new model capabilities into shipped features; your feedback shapes what gets prioritized in training.Own reliability and performance at scale: Build systems that handle millions of agentic tasks with low latency, high reliability, and the kind of correctness that developers depend on in production.Move the category forward: Cognition is defining what AI software engineering looks like. You will have real input into what gets built next and why.Exceptional Candidates Have DemonstratedSystems engineering depth: Experience building reliable, performant distributed systems; you have strong opinions about correctness, failure modes, and production behavior.Product instinct: You care about how the software you build feels to use and you have shipped things that real people depend on.Comfort with ambiguity: You can make progress on hard problems with incomplete specs, learn fast from results, and course-correct without needing a lot of direction.Velocity without shortcuts: A track record of shipping quickly while maintaining the kind of code quality that a high-density team expects.Curiosity about agents and AI: You have dug into how LLMs work, how agents fail, and what it takes to make AI-powered systems behave reliably in the real world.Strong Python proficiency: Python is the primary language across Cognition's codebase; you write clean, well-structured Python and are comfortable owning large Python codebases in production.Relevant industry experience: Prior experience at a frontier AI lab, applied AI company, or developer tools company; you know what good looks like in this category.Degree from a top-tier university: BS, MS, or equivalent in Computer Science, Mathematics, Engineering, or a related technical discipline from a highly selective program.Compensation & BenefitsBase Salary: $260,000 - $300,000 + Significant early-stage equityMedical, Dental, Vision: Fully paid for you and your dependents401(k): Company match includedPerks: Private chef, cozy slippers, endless snacks, and moreEqual 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 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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We are an AI research lab building foundational intelligence for the physical world.Our models are designed to solve complex real-world challenges, powering everything from intelligent robots to next-generation wearables and media.We work at the intersection of world models, video generation, and robotics, building systems that represent complex environments, reason about objects and dynamics, and translate high-level AI intentions into smooth, efficient, safe, and responsive actions across a variety of robotic embodiments.You will collaborate closely with ML researchers developing multimodal world models and generative systems, and with hardware teams and partners to ensure robotic platforms, sensing, and system dynamics behave optimally in real-world operation. What You’ll DoBuild the Foundation: Collaborate with our world model team to build state-of-the-art training and simulation platform for robotics.Build the "World": Develop persistent 3D/4D scene representations that maintain temporal consistency.Drive Intelligence: Unlock advanced robotics planning and decision making through our in-house, cutting-edge world models.Sim2Real: Ensure sensing and system dynamics perform reliably in high-stakes, real-world operations, where models think, simulate, and act.Push Boundaries: Partner with top ML researchers to innovate on generative models and physical AGI.Areas of InterestWe are particularly excited about candidates working on topics such as:World models for embodied systems3D / 4D generative models3D reconstruction and scene understandingEmbodied AIObject-level / semantic SLAMEmbodied AIMultimodal AI What We’re Looking ForBackground in robotics, or computer visionExperience with 3D perception, scene representations, or world modelsExperience working with robotic systems, simulation, or real-world platformsStrong programming skills (Python, C++, or similar)Ability to work across machine learning, perception, and robotics

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About UsAt LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale.With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world.Today, LangChain, LangGraph, LangSmith, and Fleet are used by teams shipping real AI products across startups and large enterprises. Millions of developers trust LangChain to power AI teams at companies like Replit, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, and 35% of the Fortune 500.About the Role: We are looking for an GTM Engineer where you won’t just be using our tools—you’ll be the "First Customer," building the AI-native systems that power our technical support, onboarding, and customer success engines.You will own the technical roadmap for how LangChain supports its users. Your goal is to drive massive case deflection and a premium onboarding experience by building autonomous agents that solve complex technical problems before a human ever needs to step in. This is a role for a builder-operator who can identify a friction point in the customer journey and ship a production-grade agentic solution to fix it.You Will:Architect Customer Agents: Design and deploy production-grade agents (using LangGraph and LangSmith) that handle technical support queries, troubleshoot integrations, and guide users through complex onboarding flows.Drive Case Deflection: Analyze customer friction points and build self-service AI systems that significantly reduce support volume while improving the quality of the customer experience.Own the Domain: Act as the product owner and the technical muscle proactively identifying opportunities for improvement, propose architectures, and own the full lifecycle of the systems you build.Dogfood the Stack: Be a key member of the feedback loop for our product team. As you build complex systems for our customers, you’ll identify gaps in our frameworks and contribute back to the LangChain and LangGraph open-source ecosystem.Build Onboarding Workflows: Develop "AI-native onboarding" experiences that help enterprise customers move from prototypes to production faster by automating documentation retrieval and code generation.What we are looking for:AI-Native Developer: You have a deep understanding of the LLM stack: prompting, retrieval (RAG), cognitive architectures, and agentic loops. You have likely already built with LangChain or LangGraph.Engineering Foundation: You are a strong software engineer (typically 3+ years) with at least 1 year of experience specifically shipping LLM systems in production.Self-Directed "Founder" Mentality: You don't need a ticket to tell you what to fix. You are comfortable navigating ambiguity, identifying high-impact problems, and driving them to completion autonomously.Full-Stack Capability: Strong coding skills in Python or TypeScript (ideally both) and the ability to build end-to-end applications.Customer-Centric: You enjoy the intersection of high-level engineering and direct customer impact. You can translate a customer's technical pain point into a scalable system architecture.Nice to Haves:Expertise with LangSmith for evaluation and monitoring.Experience building or maintaining open-source projects.A background in technical consulting, solutions engineering, or high-growth GTM teams.Compensation:We offer competitive compensation that includes base salary, meaningful equity, benefits, and perks. Benefits include things like medical, dental, and vision coverage, flexible vacation, a 401(k) plan, and life insurance.Salary: $160K - $180KCompensation Philosophy:We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. Actual compensation and offerings will vary based on role, level, and location. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations.BenefitsBenefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

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Senior Full Stack EngineerBuild the AI platform that's rewriting a $50B industry. About HaastWe're building one of the first agentic systems for enterprise legal and compliance teams that actually automates their manual work. End-to-end. Delivering 80% faster compliance reviews and 4x productivity gains.We recently closed a $12M USD Series A (Peak XV Partners, DST Global, Airtree) and are ramping hard; building the infrastructure that will completely re-define how enterprises think about compliance. Think Canva for design. Atlassian for projects. Haast for compliance. The ProblemCompliance is a $50B global challenge. Enterprise legal and compliance teams spend a significant amount of time manually reviewing documents against policy, spotting regulatory risk, and signing off on content before go-to-market. It's painful. It scales terribly. It's mission-critical.We're building the infrastructure that makes this manageable at scale. You'll be working on systems that directly reduce risk and unlock productivity for some of the world's largest organisations. The RoleThis is a full-stack role in a high-autonomy engineering team where your code ships to production and directly impacts enterprise customers. You won't be managing legacy systems, you'll be solving hard, high-stakes technical problems with real commercial impact.You'll own end-to-end technical decisions: designing systems, architecting solutions, shipping to production, and iterating based on customer feedback. You'll work directly with our founding team, move fast, and have genuine influence over how we build. What You'll OwnDesign, architect, and operate scalable services and APIs that power our LLM compliance platformArchitecting how our AI insights are surfaced to users, ensuring the system is robust, fast, and intuitive.Make high-impact technical decisions quickly. You challenge "why" and "how" to ensure we are delivering the best possible experience for our users. Shape our engineering culture, standards, and tooling as we grow Who We're Looking ForYou've built systems at meaningful scale, you write clean code with strong reasoning around design, and you genuinely care about how systems work, not just whether they runYou're deep on one or more of: Go, Node.js/TypeScript, or Python and you're comfortable enough on the frontend to contribute when it matters.You understand APIs and distributed systems in production.You've shipped in fast-moving environments. You know what it takes to move without sacrificing reliability. You're curious about how LLMs work and genuinely excited about building on top of them.Why Join HaastReal impact, day one. Your code runs inside the workflows of major global enterprises immediately. It's production-grade work solving real compliance problems.Meaningful equity upside. We're building a generational company in a $50B market. You'll own a meaningful stake in that value creation. We believe in sharing success with the team that builds it.Exceptional learning velocity. Series A is where it gets real. You'll learn more about scaling systems, working with customers, and building products in 12 months here than most roles offer in three years.Engineering-driven culture. No red tape. No performance theatre. Just shipping. We hire smart people and get out of their way.Flexibility and community. Hybrid from our Sydney office, flexible hours, and a team that actually wants to work together.How to ApplyWe're looking for people who've shipped things they're proud of and want to work on a problem that genuinely matters.Apply with:Your CVA brief note on this question: Tell us about a product that you've worked on either at work or in your personal time that you're proud of. No closing date. We review applications on a rolling basis.At Haast, we believe bold ideas come from diverse perspectives. We're committed to building a team that reflects the world we work in. Even if you don't tick every box, we'd love to hear from you.