# Forward Deployed Engineer (FDE) - SF **Company:** [OpenAI](https://scaleengineer.com/companies/openai) Forward Deployed Engineer at OpenAI leads complex, end-to-end production deployments of frontier AI models with strategic customers, bridging research breakthroughs and real-world applications. This role combines full-stack system design, customer collaboration, and direct technical delivery across multiple concurrent projects. Requires 5+ years of engineering experience with demonstrated expertise in LLM systems, production-grade code, and navigating ambiguous, high-stakes technical environments. **Role:** Forward Deployed Engineer **Seniority:** Senior **Locations:** San Francisco **Salary:** 185000–300000 USD [Apply](https://jobs.ashbyhq.com/openai/967f94aa-1706-4dba-ac89-bfbc2c38b688) Canonical: https://scaleengineer.com/jobs/openai/forward-deployed-engineer-fde-sf-967f94aa --- ## Responsibilities - End-to-End Technical Delivery Leadership: Own complete production deployment lifecycle from prototype to stable production, including system architecture, implementation, and rollout. Manage multiple concurrent deployments with strategic customers while ensuring delivery timelines and quality standards are maintained throughout the development cycle. - Full-Stack System Design and Development: Design and build full-stack systems that integrate frontier LLMs into customer workflows, balancing production reliability with experimental model capabilities. Write production-grade code across frontend and backend systems, making architectural decisions that account for model behavior and customer-specific requirements. - Customer Collaboration and Adoption Enablement: Embed directly with customer engineering and domain teams to discover requirements, guide technical adoption, and drive measurable workflow impact. Translate customer needs into technical scoping and ensure successful integration of AI solutions into their operations through close partnership and knowledge transfer. - Project Scope and Risk Management: Scope work, sequence deliverables, and proactively remove technical and organizational blockers. Make disciplined trade-offs between scope, speed, and quality while protecting delivery commitments and adjusting plans early to address emerging risks or constraints. - Hands-On Engineering Contribution: Contribute directly to codebase when progress or clarity requires it, unblocking team velocity and ensuring technical decisions align with business outcomes. Maintain coding proficiency while managing higher-level delivery responsibilities. - Knowledge Codification and Tool Development: Transform successful deployment patterns into reusable tools, playbooks, frameworks, and building blocks that scale across the organization. Document learnings and create operational tools that enable faster deployments for future projects and reduce ramp-up time. - Field Feedback and Product Roadmap Influence: Gather and synthesize real-world model behavior insights from customer deployments, identifying gaps and opportunities. Share structured feedback with Research and Product teams to directly influence model improvements and product capabilities based on production learnings. - Cross-Functional Team Coordination: Work closely with Product, Research, Partnerships, GRC, Security, and Go-To-Market teams to align deployment strategies with organizational priorities. Maintain communication clarity and follow-through across complex stakeholder landscapes to keep teams moving toward shared objectives. ## Requirements ### education - {"name":"Computer Science or Related Field","description":"Bachelor's degree in Computer Science, Software Engineering, or related technical discipline preferred. Equivalent professional experience demonstrating depth in software engineering fundamentals is valued."} - {"name":"Systems Design Knowledge","description":"Strong foundational knowledge of distributed systems concepts, scalability, performance optimization, and production architecture patterns. Self-directed learning in AI/ML systems architecture is advantageous."} ### technical - {"name":"Production-Grade Full-Stack Development","description":"Proficiency writing and reviewing production-ready code across both frontend and backend systems using Python, JavaScript, or comparable technology stacks. Strong fundamentals in software architecture, system design, and code quality standards required."} - {"name":"Large Language Model Systems Experience","description":"Hands-on experience building, deploying, or integrating systems powered by LLMs or generative models. Deep understanding of how model behavior, inference latency, token limits, and generation quality directly impact product experience and user adoption."} - {"name":"Complex Systems Architecture","description":"Demonstrated ability to design and scope complex systems in ambiguous, fast-moving environments. Experience architecting solutions that balance reliability, scalability, and feature completeness under resource and timeline constraints."} - {"name":"API Integration and System Integration","description":"Experience integrating third-party APIs and services at scale, understanding dependencies, error handling, and resilience patterns. Comfortable working with modern deployment infrastructure and managing system dependencies."} ### experience - {"name":"Senior Engineering Experience","description":"Minimum 5+ years of professional engineering or technical deployment experience with significant customer-facing components. Track record of leading or owning major technical projects from conception to production."} - {"name":"Customer-Facing Technical Roles","description":"Proven experience working directly with customers or stakeholders on technical delivery, including requirements discovery, technical consultation, and adoption support. Ability to translate between technical and business contexts seamlessly."} - {"name":"Fast-Paced, Ambiguous Environments","description":"Success shipping products and solving complex technical problems in environments with incomplete information, rapidly changing priorities, and high uncertainty. Comfort with iteration and course correction based on market or user feedback."} - {"name":"Production Incident Response and Resilience","description":"Experience managing production issues, incident response, and building systems with appropriate reliability and observability. Demonstrated ability to troubleshoot complex multi-component systems under pressure."} ## Skills ### required - {"name":"Python Development","description":"Strong expertise in Python for backend systems, data processing, and AI application development. Ability to write clean, maintainable, and performant Python code suitable for production systems."} - {"name":"JavaScript/TypeScript","description":"Proficiency in JavaScript or TypeScript for full-stack development, including modern frontend frameworks and backend runtime environments like Node.js."} - {"name":"System Design and Architecture","description":"Ability to design scalable, maintainable systems that meet both technical requirements and business constraints. Experience making architectural trade-offs and documenting design decisions."} - {"name":"Customer Collaboration and Communication","description":"Excellent communication skills across technical and non-technical audiences. Ability to gather requirements, explain complex technical concepts clearly, and build trust with external stakeholders."} - {"name":"Project Scoping and Execution","description":"Skill in breaking down complex projects into manageable components, sequencing delivery, estimating effort, and managing scope creep while protecting quality."} - {"name":"Decision-Making Under Pressure","description":"Ability to evaluate trade-offs, make sound decisions with incomplete information, and maintain composure during high-stakes situations. Strong judgment about technical and business priorities."} - {"name":"LLM Application Development","description":"Direct experience building applications powered by large language models, understanding model APIs, prompt engineering, retrieval-augmented generation, and integration patterns."} ### preferred - {"name":"Kubernetes and Container Orchestration","description":"Experience with Kubernetes, Docker, or other container orchestration platforms for managing production deployments at scale."} - {"name":"Cloud Platform Experience","description":"Familiarity with major cloud platforms such as AWS, Google Cloud, or Azure, including deployment, scaling, and infrastructure management practices."} - {"name":"Observability and Monitoring","description":"Experience designing and implementing monitoring, logging, and observability solutions for production systems. Knowledge of tools like Prometheus, Datadog, or ELK stack."} - {"name":"API Design and Development","description":"Expertise designing RESTful or gRPC APIs, understanding versioning strategies, backward compatibility, and API documentation best practices."} - {"name":"Database Design and Optimization","description":"Experience designing database schemas, optimizing queries, and choosing appropriate database technologies for different use cases (SQL, NoSQL, vector databases)."} - {"name":"Security and Compliance","description":"Understanding of application security principles, data protection, authentication/authorization patterns, and compliance requirements relevant to enterprise deployments."} - {"name":"Machine Learning Operations (MLOps)","description":"Exposure to MLOps practices including model versioning, deployment pipelines, A/B testing frameworks, and monitoring model performance in production."} - {"name":"Generative AI Ecosystem Knowledge","description":"Familiarity with the broader generative AI ecosystem including fine-tuning approaches, prompt engineering frameworks, vector databases, and emerging AI application patterns."} ## Tech stack ### tools - {"name":"Docker","description":"Containerization for consistent deployment across development, testing, and production environments."} - {"name":"Kubernetes","description":"Container orchestration for managing scalable, resilient deployments of LLM applications at scale."} - {"name":"GitHub/GitLab","description":"Version control and collaboration platform for managing codebase, code review, and deployment automation."} - {"name":"CI/CD Pipelines","description":"GitHub Actions, GitLab CI, or similar tools for automated testing, building, and deploying application updates."} - {"name":"Datadog or CloudWatch","description":"Observability and monitoring platforms for tracking system health, performance, and model behavior in production."} ### others - {"name":"OpenAI API","description":"Integration with OpenAI's GPT models, fine-tuning APIs, and embeddings for building customer applications."} - {"name":"REST APIs and gRPC","description":"Expertise in designing and consuming APIs for system integration and microservices communication."} - {"name":"Prompt Engineering","description":"Techniques for crafting effective prompts and designing prompt workflows that maximize model performance for specific use cases."} - {"name":"Inference Optimization","description":"Understanding of model serving, batching, caching strategies, and latency optimization for production LLM deployments."} ### databases - {"name":"PostgreSQL","description":"Primary relational database for storing deployment state, customer data, and operational metrics in production systems."} - {"name":"Vector Databases","description":"Specialized databases like Pinecone, Weaviate, or Milvus for semantic search and retrieval-augmented generation features in LLM applications."} - {"name":"Redis","description":"In-memory data store for caching, session management, and low-latency operations in production deployments."} ### languages - {"name":"Python","description":"Primary backend language for API development, data processing, and integration with LLM systems. Used for building deployment automation and operational tooling."} - {"name":"JavaScript/TypeScript","description":"Full-stack capability with TypeScript for type safety. Used for frontend development, backend services via Node.js, and cross-platform scripting."} ### frameworks - {"name":"FastAPI or Flask","description":"Python web frameworks for building robust REST APIs that serve LLM applications and integrate with customer systems."} - {"name":"React or Vue.js","description":"Modern frontend frameworks for building customer-facing applications and internal tools that interact with deployed models."} - {"name":"LangChain or LlamaIndex","description":"Popular frameworks for building production LLM applications with chains, agents, memory management, and retrieval-augmented generation patterns."} ## Benefits ### benefits - {"name":"Equity and Stock Options","description":"Significant equity package aligned with OpenAI's mission and growth trajectory, providing long-term wealth creation opportunity."} - {"name":"Health Insurance Coverage","description":"Comprehensive medical, dental, and vision insurance plans with employer contributions for the candidate and eligible dependents."} - {"name":"Mental Health and Wellness Programs","description":"Access to mental health services, wellness platforms, fitness programs, and counseling resources supporting employee well-being."} - {"name":"Retirement Planning","description":"401(k) matching program with employer contributions to support long-term retirement savings and financial security."} - {"name":"Paid Time Off and Vacation","description":"Generous paid vacation, sick leave, and personal days allowing for work-life balance and family time."} - {"name":"Relocation Assistance","description":"Full relocation package including moving expenses, temporary housing, and career transition support for new hires relocating to San Francisco."} - {"name":"Professional Development","description":"Learning and development budget for conferences, courses, and skill enhancement programs to support career growth."} - {"name":"Parental Leave","description":"Comprehensive parental leave policies supporting both mothers and fathers with paid time following the birth or adoption of a child."} ## Compensation - **max:** 300000 - **min:** 200000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Recruiter Screening","description":"Initial conversation with OpenAI recruiter to discuss background, experience with LLM systems, and alignment with Forward Deployed Engineering role requirements. Expect discussion of past projects involving production deployments and customer-facing technical work."} - {"name":"Technical Phone Interview","description":"Engineering-focused conversation with a current FDE or senior engineer covering system design approach, past technical challenges, and problem-solving methodology. Discussion of trade-offs made in previous projects and architectural decisions."} - {"name":"System Design Assessment","description":"Detailed technical interview focused on designing a full-stack system for an LLM-powered application. Evaluate ability to scope complexity, make architectural trade-offs, identify failure modes, and communicate design rationale clearly."} - {"name":"Customer Collaboration and Communication","description":"Behavioral interview or simulation assessing how candidates navigate ambiguity, gather requirements from stakeholders, and communicate technical concepts to non-technical audiences. May include role-play scenarios with customer-like stakeholders."} - {"name":"Case Study or Real-World Problem","description":"Discussion of or presentation on a real or hypothetical deployment challenge, evaluating problem-solving approach, risk identification, and decision-making under constraints similar to actual FDE work."} - {"name":"Interview with Leadership","description":"Conversation with team leadership or skip-level manager to assess cultural fit, long-term career aspirations, and compatibility with OpenAI's mission and values around safe AI deployment."} ## Full description **About the team** OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. **About the role** Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. **In this role you will** * Own technical delivery across multiple deployments from first prototype to stable production * Build full-stack systems that deliver customer value and sharpen how we learn * Embed closely with customer teams, understand their needs, and guide adoption of what you build * Scope work, sequence delivery, and remove blockers early * Make trade-offs between scope, speed, and quality; adjust plans to protect delivery * Contribute directly in the code when progress or clarity depends on it * Codify working patterns into tools, playbooks, or building blocks that others can use * Share field feedback that helps Research and Product understand where the models succeed and where they can improve * Keep teams moving through clarity and follow-through **You might thrive in this role if you** * Bring 5+ years of engineering or technical deployment experience that includes customer-facing work * Have scoped and delivered complex systems in fast-moving or ambiguous environments * Write and review production-grade code across frontend and backend using Python, JavaScript, or comparable stacks * Have built or deployed systems powered by LLMs or generative models and understand how model behaviour affects product experience * Simplify complexity and make fast, sound decisions under pressure * Communicate clearly with engineers, product teams, and customer stakeholders * Spot risks early and adjust without slowing down * Model calm and judgment when the stakes are high **About OpenAI** OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see [OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement](https://cdn.openai.com/policies/eeo-policy-statement.pdf). Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through [this form](https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA). No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this [link](https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241). [OpenAI Global Applicant Privacy Policy](https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf) At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.