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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, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater.About the RoleWe're looking for a Solutions Architect to join our Professional Services team. You'll work directly with enterprise customers to design, deploy, and optimize production-grade AI infrastructure and agent systems. You'll be responsible for architecting scalable, secure infrastructure deployments and building reliable, well-evaluated agent applications that solve real business problems.This role combines software development, infrastructure/platform engineering, and customer-facing skills. You'll work on everything from Kubernetes cluster design to multi-agent system architecture, requiring deep technical expertise across both infrastructure and agent engineering domains.This role offers direct impact on customer success, the opportunity to shape best practices, and work with cutting-edge AI technology. You'll join a collaborative team environment with a strong engineering culture.Key ResponsibilitiesInfrastructure & Platform Engineering: Design scalable, highly-available infrastructure for AI platform deployments (compute, storage, networking, security), enterprise integration patterns, Infrastructure as Code (Terraform, Helm), multi-region HA/DR strategies, and CI/CD pipelinesAgent Engineering & Development: Design multi-agent systems using different patterns, implement agent logic using modern frameworks (langchain/langgraph), design comprehensive evaluation frameworks, optimize prompts with A/B testing, and guide deployment/operationsCustomer Engagement & Assessment: Lead technical maturity assessments, work directly with enterprise customers to understand requirements and present recommendations, and partner with Engagement Managers and Product/Engineering teamsWhat We're Looking ForRequired Experience7+ years of experience in a technical, hands-on customer-facing roles such as Solutions Architect or Forward Deployed Engineer. We also like former founders, so if you have an unusual background, but all the right skillsets, you are welcome to applyInfrastructure & Platform:3+ years of experience designing and deploying production infrastructure on cloud platforms (GCP, AWS, or Azure)Strong Kubernetes experience (GKE, EKS, or AKS) including cluster design, autoscaling, and multi-zone deploymentsExperience with Infrastructure as Code (Terraform, Helm) and GitOps practicesKnowledge of database systems (relational databases, in-memory data stores) including HA, replication, backup strategies, and sizingExperience designing high-availability and disaster recovery solutionsStrong understanding of networking, security (SSO/RBAC, TLS, secrets management), and observability (Prometheus, Grafana, Datadog)Experience with CI/CD pipelines for infrastructure and applicationsAgent Engineering & Development:1+ years of experience building production AI/ML applications or agentsStrong experience with LLM frameworks (LangChain, LangGraph, or similar) for building agent-based applicationsExperience with state management patterns (short-term and long-term memory)Experience designing and implementing evaluation frameworks for AI applicationsStrong prompt engineering skills with experience in optimization and A/B testingExperience with vector stores, RAG patterns, and knowledge organizationExperience with tool integration, API design, and error handling patternsStrong Python and/or TypeScript development skillsCustomer-Facing:Customer-facing experience with enterprise customersExperience conducting technical assessments or infrastructure auditsStrong communication skills with ability to explain technical concepts to diverse audiencesKey AttributesStrong problem-solving skills with ability to analyze complex requirements and design elegant solutionsExcellent customer-facing communication skills, able to explain technical concepts to diverse audiencesExperience working cross-functionally with engineering teams, product teams, and customersConsultative approach with ability to understand customer needs, provide recommendations, and guide implementationAbility to balance infrastructure architecture with agent development workStrong engineering background with hands-on development experienceLocation: Singapore Compensation 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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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs a Senior Member of Technical Staff, Machine Learning, you are an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale.This is a hands-on, high-impact role focused on depth. FocusBuild core ML systems that power a proactive, long-horizon AI product.Own work end-to-end: data preparation, training, evaluation, inference, and iteration.Turn research ideas into working systems that run reliably in production.Debug model failures and system issues using real production signals.Iterate quickly: ship, measure outcomes, refine, and repeat.Collaborate closely with research, product, and engineering to deliver real user impact.Mentor and review work from other ML engineers through example and technical judgment.Work under real production constraints: latency, cost, reliability, and safety Tech StackPythonPyTorch / JAXGPU-based training and inference systems Ideal ExperienceYou have built and shipped ML systems used by real users.You understand how modern ML models behave — and misbehave — in production.You write strong, production-quality code and think in systems, not scripts.You take ownership, work independently, and push work across the finish line.You learn fast, communicate clearly, and improve through iteration. OutcomesML models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets.Complex production issues are monitored, debugged, and resolved with minimal disruption.Training, inference, and data pipelines are robust, scalable, and maintainable over time.Drives measurable improvements in ML systems based on real-world signals and user feedback.Provides mentorship and technical guidance to peers, raising the overall ML engineering standard.Collaborates cross-functionally to ensure ML features integrate seamlessly into products and meet business goals. How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.RoleYou will explore and build experimental AI experiences that help define how people interact with proactive AI systems. This role sits at the intersection of design, engineering, and AI experimentation.This is not a research-only role. You will build prototypes, test ideas, and help the team decide which interaction models should become part of the product.What You'll Be DoingPrototype experimental AI interfaces beyond standard chat UI.Build quick proof-of-concept experiences using AI models, APIs, and frontend tools.Explore new ways for users to understand, direct, and collaborate with AI systems.Test interaction ideas around human control, trust, transparency, memory, multimodal input, and long-running workflows.Work with product, design, and ML teams to turn early ideas into testable prototypes quickly.Identify useful HCI patterns from research, products, and emerging tools, then test whether they work for A1.Document experiments clearly - what was tested, what worked, what failed, and what should be built next.Contribute to the team's understanding of what HCI should look and feel like in a real consumer app.What You Will NeedExperience prototyping at the intersection of design and technology - creative technology, design engineering, prototyping, or R&D roles.Ability to build functional prototypes using web technologies, APIs, or AI tools.Curiosity about how AI systems work and how users build mental models of AI behavior.Comfort moving between design thinking and hands-on building.Awareness of HCI principles, emerging UI patterns, and the limitations of current AI systems.Strong communication skills - able to explain experimental ideas and prototype findings clearly.High comfort with ambiguity and early-stage product exploration.Good judgment on which experiments are interesting versus which ones are actually useful for users. How We WorkThe best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs a Member of Technical Staff, Machine Learning, you will build core ML components. You will work on real production systems from day one, learning how large-scale ML behaves outside of research settings.This role is for engineers who want to develop strong systems judgment by shipping, debugging, and iterating on real-world ML. FocusBuild and improve ML components across data, training, evaluation, and inference.Fine-tune and adapt models as part of larger production systems.Implement evaluation and testing to understand model behavior.Help build and maintain data pipelines for real-world and synthetic data.Debug model issues, performance problems, and production incidents.Ship improvements iteratively and learn from real user feedback.Work closely with senior ML engineers and product teams.Work under real production constraints: latency, cost, reliability, and safety Tech StackPythonPyTorch / JAXProduction ML systems running on GPUs Ideal ExperienceStrong foundations in machine learning and modern neural architectures.Some hands-on experience training, fine-tuning, or deploying ML models.Comfortable writing production-quality code and learning new tools quickly.Curious, coachable, and eager to learn from real systems in production.Able to work through ambiguity with guidance and grow ownership over time.Bias toward shipping, iteration, and continuous improvement. OutcomesML models in production meet expected accuracy, latency, and reliability targets.Production issues are identified quickly, debugged effectively, and root causes addressed.Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.Iterations on models and systems are driven by real-world signals and measurable improvements. How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs Technical Lead, Machine Learning, you own the execution layer of A1’s intelligence. You translate research direction into reliable, scalable, production-grade ML systems.This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints.What You'll DoOwn end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.Architect and operate scalable inference systems, balancing latency, cost, and reliability.Design and maintain data systems for high-quality synthetic and real-world training data.Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.Make pragmatic trade-offs and ship improvements quickly, learning from real usage.Work under real production constraints: latency, cost, reliability, and safetyOutcomesResearch and models reliably translate into production-ready solutions with clear performance and quality targets.ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.Production issues are detected, debugged, and resolved quickly, minimizing user impact.Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.Iterations on models and systems are measurable, safe, and improve user experience over time.Tech StackPythonPyTorch / JAXGPU-based training and inference systemIdeal ExperienceYou have built or shipped real ML systems used by people, not just demos.You are comfortable working with large models and understanding their failure modes.You write strong, production-grade code and care about system correctness.You are self-directed, pragmatic, and take full ownership of outcomes.You communicate clearly and collaborate well in small, high-trust teams.How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical productInterview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.RoleAs an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production.This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage. FocusBuild and ship AI features end-to-end (model → system → user experience)Design and iterate on prompts, tools, memory, and agent workflowsTurn raw model outputs into structured, reliable, and predictable behaviorsDebug issues across the full stack (model, orchestration, infra, UX)Optimize for latency, cost, and production reliabilityDevelop lightweight evaluation frameworks to measure real-world performanceWork closely with product and engineering to translate ambiguous problems into working systems Tech StackPythonPyTorch / JAXLLMs (OpenAI-style APIs, LLaMA, Qwen, etc.)Inference / serving (e.g. vLLM)Vector DB Ideal ExperienceStrong foundation in machine learning and modern neural network architectures.Hands-on experience with training, fine-tuning, or deploying ML modelsAbility to write clean, production-quality codeComfort working across abstraction layers (model → infra → product)Strong problem-solving skills in ambiguous, fast-moving environmentsBias toward shipping, iteration, and continuous improvement OutcomesML models in production meet expected accuracy, latency, and reliability targets.Production issues are identified quickly, debugged effectively, and root causes addressed.Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.Iterations on models and systems are driven by real-world signals and measurable improvements. How We Work The best products today in the world were built by small, world class teams. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical AI product.  Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleThis is a deeply technical, hands-on role. Work directly with engineers on system design, evaluation, and trade-offs-defining requirements, but shaping how the system works for global users. You work at the intersection of user needs, model capability, and system constraints, and are responsible for turning AI potential into real, reliable behavior in a real-world application.  What You'll be DoingResearch and define end-to-end AI system requirements from capability to behavior to user impactTranslate model capabilities, data constraints, and evaluation results into clear product and system decisionsMake hard trade-offs across quality, latency, cost, reliability, and UXWork closely with ML, backend, and mobile engineers on system design, evaluation, and iterationDefine and evolve evaluation frameworks across offline metrics, online experiments, and human feedbackDrive execution with clear specs, strong judgment, and disciplined prioritizationEnsure systems ship quickly, safely, and reliably, with strong feedback loopsOwn product quality end-to-end - correctness, predictability, and user trust What You Will NeedTechnical foundationStrong grounding in computer science fundamentals, including algorithms, data structures, and system design.Solid understanding of ML fundamentals and how modern AI systems behave in production.Comfort reading, reviewing, and discussing technical design documents.AI & ML experienceHands-on exposure to AI-powered products, including LLM-based systems.Experience working with model evaluation, prompt or pipeline iteration, and feedback loops.Strong intuition for model limitations, hallucinations, bias, and drift.Product leadershipSignificant experience owning complex, technical products end-to-end.Proven ability to work closely with senior engineers and ML teams.Strong judgment and decision-making ability in ambiguous, fast-moving environments.Ability to balance ambition with technical and operational reality. Nice to haveExperience shipping AI-heavy consumer products.Background as an engineer or highly technical product manager.Experience defining evaluation metrics for ML systems.Strong intuition for AI UX patterns and failure handling.Prior experience in zero-to-one product environments. OutcomesProduct strategy clearly aligns AI capabilities with user needs and company priorities.AI features deliver real value, are understandable, predictable, and trusted by users.Decisions balance quality, speed, cost, and reliability effectively under uncertainty.Roadmaps and priorities are clear, with fast iteration based on real user feedback.Teams are aligned, focused, and able to execute on AI product goals with minimal friction. How We WorkThe best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product. Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs a Backend Engineer, AI, you own the inference and orchestration layer that powers every AI interaction in the product. Your work sits between models and users, where latency, correctness, reliability, and cost directly impact real-world experience.You will build and operate production systems that turn model capability into fast, stable, observable APIs used across mobile and desktop clients. FocusBuild and operate backend systems that serve AI-powered features in production.Design inference pipelines, orchestration layers, and service boundaries around models.Own production concerns: monitoring, logging, alerting, and incident response.Optimize latency and throughput across inference, caching, batching, and streaming. Ideal ExperiencesStrong backend engineering fundamentals in production environments.Experience running high-throughput, low-latency services.Familiarity with AI inference patterns (LLMs, embeddings, multimodal).Comfortable debugging distributed systems under load.Bias toward shipping and learning from production behavior. OutcomesBackend systems run reliably at scale, handling production AI traffic with low latency and high throughput.APIs are stable, clear, and support seamless integration with frontend and ML systems.Production incidents are quickly detected, diagnosed, and resolved, minimizing user impact.Iterative improvements based on real usage continuously increase system performance and reliability. Tech StackPythonNodeJsPytorchOpenAI / Anthropic / open-source LLMsSQl & noSQLKubernetesDocker How We WorkThe best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs Technical Lead, Machine Learning, you own the execution layer of A1’s intelligence. You translate research direction into reliable, scalable, production-grade ML systems.This role sits at the intersection of research, infrastructure, and product. You are responsible for making models trainable, deployable, observable, and performant under real-world constraints.What You'll DoOwn end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.Architect and operate scalable inference systems, balancing latency, cost, and reliability.Design and maintain data systems for high-quality synthetic and real-world training data.Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.Make pragmatic trade-offs and ship improvements quickly, learning from real usage.Work under real production constraints: latency, cost, reliability, and safetyOutcomesResearch and models reliably translate into production-ready solutions with clear performance and quality targets.ML pipelines, training loops, and inference systems are stable, efficient, and maintainable.Production issues are detected, debugged, and resolved quickly, minimizing user impact.Team members are supported, aligned, and able to deliver high-impact ML work with minimal friction.Iterations on models and systems are measurable, safe, and improve user experience over time.Tech StackPythonPyTorch / JAXGPU-based training and inference systemIdeal ExperienceYou have built or shipped real ML systems used by people, not just demos.You are comfortable working with large models and understanding their failure modes.You write strong, production-grade code and care about system correctness.You are self-directed, pragmatic, and take full ownership of outcomes.You communicate clearly and collaborate well in small, high-trust teams.How We Work The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical productInterview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. RoleAs an Android Software Engineer, you own the Android client experience, how AI feels, behaves, and performs on mobile devices. This is not a thin client role. You will build a production Android application where AI interactions are core to the product, and performance, reliability, and clarity matter. FocusBuild and maintain production Android apps using Kotlin.Integrate AI-powered features (chat, vision, voice, recommendations) via backend APIs.Design UX patterns for AI interactions, including streaming responses, retries, and partial results.Optimize performance, memory usage, and responsiveness for AI-heavy flows.Implement analytics, logging, and feedback capture to support AI evaluation and iteration.Collaborate closely with backend and ML engineers on API contracts and system behavior.Ensure app stability, security, and scalability in production environments. Ideal Experiences3+ years of Android development experience using Kotlin.Hands-on experience integrating AI features (e.g. LLM, vision, speech APIs).Strong understanding of asynchronous programming (Coroutines, Flow).Familiarity with REST or gRPC APIs and structured data formats.Strong debugging and performance profiling skills.Comfort building in environments with latency, partial failure, and non-deterministic behavior.Experience with MLKit or light on-device inference.Published production apps on the Google Play Store. OutcomesStable, smooth, and reliable real-world use android applications.Performance is optimized: responsive, low-latency, and efficient on memory and CPU.Production issues are detected early, monitored effectively, and resolved with clear root-cause analysis. Tech StackKotlin / JavaSQL / noSQLTensorFlow Lite (on-device inference) How We WorkThe best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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CompanyA1 is building a proactive AI smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior.RoleWe are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users. FocusBuild end-to-end product features across frontend, backend, and AI integrationsDesign agent workflows that handle planning, tool use, failure, and recovery across multiple steps.Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditionsDesign real-time AI interactions with streaming, partial results, and tight latency constraintsImprove system reliability, observability, and fallback mechanismsCollaborate closely with ML, backend, and product teams to ship features end-to-endContinuously iterate based on real usage and failure modes Ideal ExperiencesStrong experience in full stack engineering (frontend + backend)Solid understanding of system design and API architectureExperience working with LLMs, RAG systems, or AI-powered applicationsAbility to handle ambiguity and make pragmatic engineering decisionsStrong ownership - able to take features from idea to productionComfort working in fast-moving environments with evolving requirements OutcomesOwn and ship AI-native product features that move beyond chat into persistent, goal-driven workflowsDesign and deploy agent workflows that reliably complete multi-step tasks across tools and sessionsReduce latency and improve responsiveness of AI interactions while maintaining output qualityBuild robust fallback and recovery mechanisms for LLM and tool failures in production environmentsImprove the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoringEstablish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systemsContribute to a product experience where AI feels proactive, consistent, and dependable over time Tech StackNext.jsPythonNodeJsPytorchOpenAI / Anthropic / open-source LLMsSQl & noSQLKubernetesDocker How We WorkThe best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product Interview processIf there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.We're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.We're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.If you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.About the Role:As we scale our AI infrastructure, we are investing deeply in the software systems that manage, observe, and heal our network at scale. We are hiring a Senior Engineering Manager, SDN Management Plane to lead the team responsible for the automation, observability, configuration management, and policy enforcement layer that runs across our entire network fleet.This is a senior software engineering leadership role. The Management Plane is the horizontal layer that ties together our control and data plane systems, making our network self-aware, self-healing, and continuously verifiable. You will lead a team of senior and staff software engineers while remaining deeply engaged in platform architecture, systems design, and the technical roadmap.This is not a network operations or SRE role. It is a platform engineering leadership position where your primary output is software: automation systems, observability pipelines, configuration management platforms, and the tooling that eliminates manual toil at scale. You will apply sound software engineering principles to hard networking problems, including the application of GenAI and machine learning to network operations.What You'll Be Working On:Platform Architecture & EngineeringOwn the architecture, development, and production operation of Crusoe's SDN Management Plane, the automation and observability layer that manages our network fleet across all regions.Build and operate CI/CD pipelines for network configuration: automated testing, policy validation, and push-on-green delivery of network changes from intent to production.Design and implement the software systems that enforce reconciliation between declared and actual network state, detect configuration drift, and trigger automated remediation workflows.Define provisioning and onboarding automation for new nodes, regions, and customer environments, ensuring consistent, policy-compliant network configuration at scale.Observability and Intelligent OperationsDrive the design of network observability systems including streaming telemetry (gNMI/gRPC), synthetic probing, anomaly detection, and real-time traffic monitoring across GPU clusters.Design and implement self-healing network capabilities: closed-loop automation with appropriate guardrails that detects, diagnoses, and resolves network faults without human intervention.Set the technical vision for applying GenAI and machine learning to network operations, from intelligent anomaly detection to natural-language-driven network management.Cross-Functional PartnershipPartner closely with Control Plane and Data Plane teams to ensure clean software interfaces between layers, and with infrastructure and compute teams to support GPU cluster networking requirements.Act as the internal platform owner for network automation: treat other engineering teams as customers with real product requirements, not just consumers of scripts.People LeadershipLead, mentor, and grow a team of senior and staff-level software and network automation engineers.Set technical standards, review architecture and design decisions, own team performance and development.Foster a high-ownership engineering culture focused on shipping production software, not just maintaining tooling.What You'll Bring to the Team:10+ years of experience in network software engineering, network automation platform engineering, or infrastructure platform engineering.5 to 7+ years managing senior and staff-level software engineers, with demonstrated ability to build and scale a platform team.Proven track record of architecting and shipping production-grade automation and observability systems, not just configuring or consuming existing tooling.Deep hands-on experience building network automation platforms: architecting and owning systems that other engineering teams depend on as internal customers.Strong fluency in network automation frameworks and tooling: Ansible, Nornir, Napalm, Salt, or equivalent. Proven experience building production CI/CD pipelines for network infrastructure, including test coverage, rollback logic, and policy validation.Experience with network source-of-truth systems (NetBox, Nautobot, or custom CMDB) and building software-driven reconciliation loops between declared and observed network state.Familiarity with network telemetry and observability systems: gNMI, gRPC streaming telemetry, OpenTelemetry, or equivalent synthetic probing and monitoring architectures.Solid understanding of network protocols and SDN architectures: BGP, VXLAN, EVPN, and familiarity with control plane systems (OVN/OVS preferred) at the level needed to automate them effectively.Experience with network modeling standards: YANG, Netconf, RESTCONF, or intent-based networking abstractions.Strong software engineering background with fluency in Python and/or Go. Able to set code quality standards, define testing strategies, and review complex platform code at a staff engineer level.Demonstrated ability to lead in fast-moving, execution-heavy environments: comfortable building from scratch, shipping iteratively, and owning production systems end-to-end.Track record of managing platform teams with internal customers, able to balance roadmap commitments with operational reliability and stakeholder needs.Clear platform mindset: you have built software that other teams depend on, defined its interfaces, and owned its reliability as a product.Bonus PointsExperience applying GenAI, ML, or AIOps techniques to network operations: anomaly detection, predictive failure analysis, or natural-language configuration interfaces.Background in AI infrastructure or GPU cluster networking environments.Contributions to open-source network automation or observability projects.Experience with release management and change control systems for large-scale network infrastructure.Familiarity with RDMA/RoCE or high-performance networking in GPU environments.P4 or programmable networking pipeline experience.Benefits:Industry competitive payRestricted Stock Units in a fast growing, well-funded technology companyHealth insurance package options that include HDHP and PPO, vision, and dental for you and your dependentsEmployer contributions to HSA accountsPaid Parental LeavePaid life insurance, short-term and long-term disabilityTeladoc401(k) with a 100% match up to 4% of salaryGenerous paid time off and holiday scheduleCell phone reimbursementTuition reimbursementSubscription to the Calm appMetLife LegalCompany paid commuter benefit; $300/monthCompensation RangeCompensation will be paid in the range of up to $237,000 – $288,000 + Bonus. Restricted Stock Units are included in all offers. Compensation to be determined by the applicant's knowledge, education, and abilities, as well as internal equity and alignment with market data.Crusoe is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/ orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.

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About IdeogramIdeogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship. Explore Ideogram 3.0, Character and Custom Models blog posts, and try Ideogram at ideogram.ai.The OpportunityIn this role, you'll push the frontier of visual generative models. You’ll work on large-scale pre-training for our text-to-image foundation models, shaping objectives, algorithms, data, and systems, and turn novel ideas into models that power products used by millions of users. You'll work with a creative and ambitious team of researchers and engineers who are building the future of the creative economy. What We're Looking ForPhD or Master’s degree in Computer Science or equivalent industry experience.5+ years of experience in AI research, including training, fine-tuning, and experimenting with foundation models beyond black-box use.Track record of first-author publications at top-tier AI conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ECCV, ICCV, ACL, EMNLP).Strong proficiency in one or more deep learning frameworks (e.g., JAX, PyTorch).Experience communicating complex research to peers.Solid knowledge of programming languages and experience in developing, debugging, and optimizing beyond ML systems.Our CultureWe’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.What We Offer💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success. 🌴 4 weeks of vacation to recharge and explore. 🩺 Comprehensive health, vision, and dental coverage starting on day one. 💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join. 💻 Top-of-the-line tools and tech to fuel your creativity and productivity. 📍 Toronto HQ perks: Steps from Union Station and the PATH, with daily in-office lunches and dinners. 🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking. 🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey.

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About IdeogramIdeogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship. Explore Ideogram 3.0, Character and Custom Models blog posts, and try Ideogram at ideogram.ai.About The RoleAs a Full-Stack Product Engineer at Ideogram, you'll build the products that put generative AI directly into the hands of creators. You'll work across the entire stack, from crafting delightful user experiences to optimizing backend systems that serve millions, with a relentless focus on shipping features that users love. We're looking for someone who combines product instinct with strong ownership, user empathy, and the ability to move fast in an evolving AI landscape.What We're Looking ForProduct & AI MindsetDeep curiosity about generative AI and genuine excitement about its potential to empower creatorsStrong product intuition; you think about user problems first, then architect solutionsExperience building features where AI is core to the user experience (not just a backend detail)Ability to navigate ambiguity and turn open-ended problems into shipped featuresAI-Native Full Stack ExecutionExperience building and shipping full stack applications with real user impactComfortable working across frontend and backend systemsFamiliarity with cloud infrastructure and modern web technologiesCan design APIs and data models that support evolving product needsUse AI-native engineering tools (e.g., Claude Code, Codex, or similar) to meaningfully accelerate development velocity, debugging, and codebase comprehensionOwnership & ExecutionSelf-starter who takes initiative to identify opportunities and drive them to completionOperates with urgency. You ship incremental value and iterate based on real user feedbackComfortable working with minimal direction in a fast-moving environmentTakes responsibility for outcomes, not just code—you care about whether users love what you buildCollaboration & CommunicationCan explain technical concepts to both engineers and non-technical stakeholdersSeeks feedback, acknowledges mistakes, and learns quicklyPushes for quality through constructive code review and collaborationBachelor's degree in Computer Science, Engineering, related field, or equivalent practical experienceOur StackWe primarily use React and Python. Familiarity with the following technologies is a plus, but not required:OpenAPI & gRPCKubernetesRedis & MemcachedGCP, Google Bigtable, Google BigQuery, Google Spanner, Google Pub/SubDocker & TerraformCloudflareNice to HaveExperience integrating ML models into production applications (inference, prompt engineering, fine-tuning workflows)Track record of shipping consumer-facing AI products or featuresContributions to design systems, component libraries, or developer toolingExperience with experimentation frameworks and feature flaggingFamiliarity with real-time systems or high-throughput applicationsOur CultureWe’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.What We Offer💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success. 🌴 4 weeks of vacation to recharge and explore. 🩺 Comprehensive health, vision, and dental coverage starting on day one. 💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join. 💻 Top-of-the-line tools and tech to fuel your creativity and productivity. 📍 Toronto HQ perks: Steps from Union Station and the PATH, with daily in-office lunches and dinners. 🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking. 🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey.

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About IdeogramIdeogram’s mission is to make world-class design accessible to everyone, multiplying human creativity. We build proprietary generative media models and AI native creative workflows, tackling unsolved challenges in graphic design. Our team includes builders with a track record of technology breakthroughs including early research in Diffusion Models, Google’s Imagen, and Imagen Video. We care about design, taste, and craft as much as research and engineering – shipping experiences that creatives actually love.We’ve raised nearly $100M, led by Andreessen Horowitz and Index Ventures. Headquartered in Toronto with a growing team in NYC, we're scaling fast, aiming to triple over the next year. We're a flat team with a culture of high ownership, collaboration, and mentorship. Explore Ideogram 3.0, Character and Custom Models blog posts, and try Ideogram at ideogram.ai.About The RoleWe're seeking an experienced engineer to join our team as a Software Engineer, ML Data Infrastructure. You’ll collaborate with exceptional engineers to build cutting-edge AI design experiences that delight millions of users.You'll thrive here if you're excited about:Tackling complex technical challenges collaboratively, from scaling distributed systems to enabling new generative media experiencesBuilding robust data infrastructure that powers foundation models at petabyte scale, ensuring reliability and performance across multi-modal training pipelinesOptimizing data processing workflows for massive throughput, working hands-on with distributed systems, TPU infrastructure, and large-scale storage solutionsPartnering with research scientists to understand data requirements and translating them into production-grade systems that accelerate model development cyclesWhat We're Looking ForTechnical Excellence2-5 years developing and shipping large-scale distributed systems with proven ability to manage complexity through thoughtful abstractions and scalable designStrong fundamentals in data structures, algorithms, and distributed systemsStrong understanding of databases and data storage architectures.Hands-on experience with large-scale data processing systems.Demonstrated ability to drive projects from 0 to 1, including scoping, execution, and iteration.OwnershipDeep sense of ownership - proactively identifies opportunities, suggests improvements, and acts on themThrives in fast-moving, ambiguous environments with a strong bias toward actionAsks great questions, thinks from first principles, and seeks out resources to deepen understandingOur StackOur backend infrastructure is primarily written in Python and makes use of the following technologies (experience with them is helpful but not strictly required):KubernetesGCP, Google Bigtable, Google BigQuery, Google Spanner, Google Pub/SubDocker & TerraformOur CultureWe’re a team of exceptionally talented, curious builders who love solving tough problems and turning bold ideas into reality. We move fast, collaborate deeply, and operate without unnecessary hierarchy, because we believe the best ideas can come from anyone.Everyone at Ideogram rolls up their sleeves to make our products and our customers successful. We thrive on curiosity, creativity, and shared ownership. We believe that small, dedicated teams working together with trust and purpose can move faster, think bigger, and create amazing things.Ideogram is committed to welcoming everyone — regardless of gender identity, orientation, or expression. Our mission is to create belonging and remove barriers so everyone can create boldly.What We Offer💸Competitive compensation and equity designed to recognize the value and impact of your contributions to Ideogram’s success. 🌴 4 weeks of vacation to recharge and explore. 🩺 Comprehensive health, vision, and dental coverage starting on day one. 💰 RRSP/401(k) with employer match up to 4% to invest in your future from the moment you join. 💻 Top-of-the-line tools and tech to fuel your creativity and productivity. 📍 Toronto HQ perks: Steps from Union Station and the PATH, with daily in-office lunches and dinners. 🔍 Autonomy to explore and experiment — whether you’re testing new ideas, running large-scale experiments, or diving into research, you’ll have access to compute/resources you need when there’s a clear business or creative use case. We encourage curiosity and bold thinking. 🌱 A culture of learning and growth, where curiosity is encouraged and mentorship is part of the journey.

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As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Participate in on-call rotation (Pagerduty) to respond to production incidents Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI's infrastructure Requirements 5+ years of professional AI Infra or related experience Bachelor's degree in Computer Science or a related field or equivalent work experience Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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As an AI Infrastructure Engineer at Together, you are responsible for keeping all user-facing services and production systems running smoothly. You are a blend of a pragmatic operator and a software engineer that applies sound engineering principles, operational discipline, and mature automation to our operating environments and codebase. You specialize in systems (operating systems, storage subsystems, networking), while implementing best practices for availability, reliability and scalability, with varied interests in algorithms and distributed systems. Responsibilities Participate in on-call rotation (Pagerduty) to respond to production incidents Build and run our infrastructure with Ansible, Terraform, and Kubernetes to enable scaling to a massive number of concurrent users Build monitoring systems to ensure the highest quality service for our customers Design and implement operational processes (such as deployments and upgrades) Debug production issues across all services and levels of the stack Identify improvements for the product architecture from the reliability, performance and availability perspectives Plan the growth of Together AI's infrastructure Requirements 5+ years of professional AI Infra or related experience Bachelor's degree in Computer Science or a related field or equivalent work experience Knowledge of Ansible (roles, playbooks), Terraform, and Kubernetes Proficiency in programming/scripting languages Direct experience in monitoring and observability practices Knowledge of cloud services Ability to thrive in a collaborative environment involving different stakeholders and subject matter experts About Together AI Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers and engineers in our journey in building the next generation AI infrastructure. Compensation We offer competitive compensation, startup equity, health insurance and other competitive benefits. The US base salary range for this full-time position is: $190,000 - $270,000 + equity + benefits. Our salary ranges are determined by location, level and role. Individual compensation will be determined by experience, skills, and job-related knowledge. Equal Opportunity Together AI is an Equal Opportunity Employer and is proud to offer equal employment opportunity to everyone regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, and more.

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Why Faculty? We established Faculty in 2014 because we thought that AI would be the most important technology of our time. Since then, we’ve worked with over 350 global customers to transform their performance through human-centric AI. You can read about our real-world impact here.We don’t chase hype cycles. We innovate, build and deploy responsible AI which moves the needle - and we know a thing or two about doing it well. We bring an unparalleled depth of technical, product and delivery expertise to our clients who span government, finance, retail, energy, life sciences and defence.Our business, and reputation, is growing fast and we’re always on the lookout for individuals who share our intellectual curiosity and desire to build a positive legacy through technology.AI is an epoch-defining technology, join a company where you’ll be empowered to envision its most powerful applications, and to make them happen. About the teamOur Retail and Consumer experts are dedicated to helping clients in an industry which is being transformed by new technologies and evolving consumer expectations. Leveraging over a decade of experience in Applied AI, we combine exceptional technical and delivery expertise to empower businesses to adapt and thrive. #LI-PRIOAbout the roleAs a Lead Data Scientist, you'll take on a pivotal, entrepreneurial role, functioning as the technical expert who thrives on complexity and commercial impact. You will be responsible for setting the technical direction and ensuring the high-quality, scalable delivery of our most challenging, high-impact projects. This position combines deep expertise in machine learning with strategic oversight to define project roadmaps, manage technical risk, and architect reliable solutions. Your focus will be on driving innovation, mentoring cross-functional teams, and actively shaping both our technical standards and long-term customer relationships.What you'll be doing:Setting the technical direction for complex, business-critical projects and expertly balancing trade-offs between speed, innovation, and reliability.Designing and implementing reliable, production-grade technical solutions, ensuring comprehensive documentation of architectures and specifications.Defining project problems, developing clear roadmaps, and overseeing end-to-end delivery across multi-disciplinary workstreams.Leading technical scoping and feasibility studies for high-value sales opportunities and strategic customer engagements.Managing relationships and communications with demanding clients, fostering trust and aligning technical solutions with shared long-term commercial goals.Driving the adoption of best practices, shared resources, and robust technical processes across the wider Data Science craft.Mentoring and developing other data scientists and team members, actively contributing to the growth and technical excellence of the organisation.Who we're looking for:You bring depth of expertise in at least one machine learning domain and strong technical breadth across the entire data science landscape.You are a skilled technical leader, proficient in mentoring individuals, managing teams (including other managers), and rolling out impactful tools and workflows.You have proven project management expertise, capable of dividing complex, ill-defined problems into actionable, clearly defined workstreams with timelines you can defend.You are adept at managing ill-defined, high-risk tasks, consistently delivering innovative and practical outcomes under commercial pressure.You possess strong customer leadership skills, able to act as a trusted technical advisor and drive long-term strategic relationships with demanding clients.You excel at cross-functional collaboration, effectively aligning technical strategy with Engineering, Commercial (BD), and Infrastructure teams.You have experience extending technical oversight to business unit-level initiatives, using your vision to influence and contribute to organisational success.Our Interview ProcessTalent Team Screen (30 minutes)Introduction to the team (30 minutes)Take Home Technical Assessment Technical Interview (90 minutes) Commercial Interview (60 minutes)Our Recruitment EthosWe aim to grow the best team - not the most similar one. We know that diversity of individuals fosters diversity of thought, and that strengthens our principle of seeking truth. And we know from experience that diverse teams deliver better work, relevant to the world in which we live. We’re united by a deep intellectual curiosity and desire to use our abilities for measurable positive impact. We strongly encourage applications from people of all backgrounds, ethnicities, genders, religions and sexual orientations.Some of our standout benefits:Unlimited Annual Leave PolicyPrivate healthcare and dentalEnhanced parental leaveFamily-Friendly Flexibility & Flexible workingSanctus CoachingHybrid WorkingIf you don’t feel you meet all the requirements, but are excited by the role and know you bring some key strengths, please don't hesitate in applying as you might be right for this role, or other roles. We are open to conversations about part-time hours.

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Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.

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Role Overview Scale’s rapidly growing Global Public Sector team is focused on using AI to address critical challenges facing the public sector around the world. Our core work consists of: Creating custom AI applications that will impact millions of citizens Generating high-quality training data for national LLMs Upskilling and advisory services to spread the impact of AI As a Production AI Ops Lead, you will design and develop the production lifecycle of full-stack AI applications, while supporting end-to-end system reliability, real-time inference observability, sovereign data orchestration, high-security software integration, and the resilient cloud infrastructure required for our international government partners. At Scale, we’re not just building AI solutions—we’re enabling the public sector to transform their operations and better serve citizens through cutting-edge technology. If you’re ready to shape the future of AI in the public sector and be a founding member of our team, we’d love to hear from you. You will: Own the production outcome: Take full accountability for the long-term performance and reliability of AI use cases deployed across international government agencies. Ensure Full-Stack integrity: Oversee the end-to-end health of the platform, ensuring seamless integration between the AI core and all full-stack components, from APIs to UI, to maintain a responsive and production-ready environment. Scale the feedback loop: Build automated systems to monitor model performance and data drift across geographically dispersed environments, ensuring the right levels of reliability. Navigate global compliance: Manage the technical lifecycle within diverse regulatory frameworks. Incident command: Lead the response for production issues in mission-critical environments, ensuring rapid resolution and building the guardrails to prevent them from happening again. Bridge the gap: Translate deep technical performance metrics into clear insights for senior international government officials. Drive product evolution: Partner with our Engineering and ML teams to ensure the lessons learned in the field directly influence the technical architecture and decisions of future use cases. Ideally, you have: Experience: 6+ years in a high-impact technical role (SRE, FDE or MLOps) with experience in the public sector. Global perspective: Familiarity with international government security standards and the complexities of deploying sovereign AI. System architecture proficiency: Proven experience maintaining production-grade applications with a deep understanding of the full request lifecycle-connecting frontend/API layers to the backend and AI core. Modern AI Stack expertise: Proficiency in coding and the modern AI infrastructure, including Kubernetes, vector databases, agentic development, and LLM observability tools. Ownership: You treat every production deployment as your own. You race toward solving hard problems before the customer even sees them. Reliability: You understand that in the public sector, a model failure may be a risk to public safety or privacy. Customer communication: The ability to explain to a high-ranking official why the performance of the system has degraded and how we are fixing it. PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. About Us: At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. We comply with the United States Department of Labor's Pay Transparency provision.  PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.