# Forward Deployed Engineer (FDE) - Seattle **Company:** [OpenAI](https://scaleengineer.com/companies/openai) Forward Deployed Engineers at OpenAI lead complex end-to-end production deployments of frontier large language models and generative AI systems alongside strategic customers, owning technical delivery from discovery through stable production rollout. This role requires 5+ years of full-stack engineering experience with proven expertise in building and deploying LLM-powered systems, customer-facing technical delivery, and rapid decision-making in ambiguous environments. You will bridge product innovation and customer success, directly shaping OpenAI's model and product roadmaps through field feedback while managing 50% travel and hybrid work in Seattle. **Role:** Forward Deployed Engineer **Seniority:** Senior **Locations:** Seattle **Salary:** 185000–300000 USD [Apply](https://jobs.ashbyhq.com/openai/7f4c5eef-37f9-4454-a1fb-ef1e66b075d9) Canonical: https://scaleengineer.com/jobs/openai/forward-deployed-engineer-fde-seattle-7f4c5eef --- ## Responsibilities - Own End-to-End Technical Delivery: Lead and own complete deployment lifecycle for frontier models in production, spanning from initial prototype and discovery phase through architecture design, implementation, testing, and stable production rollout alongside OpenAI's most strategic customers - Build Full-Stack Production Systems: Design and implement comprehensive full-stack systems that integrate large language models and generative AI capabilities into customer workflows, delivering measurable business value while creating feedback mechanisms for continuous model and product improvement - Customer Technical Engagement: Embed closely with customer engineering and domain teams to deeply understand their technical requirements and business objectives, guide LLM adoption, provide hands-on technical mentorship, and ensure successful integration of frontier models into production systems - Project Scoping and Delivery Management: Define project scope, sequence delivery milestones, identify and remove technical blockers early, make data-driven trade-offs between scope, speed, and code quality, and adjust plans proactively to protect on-time delivery - Hands-On Development: Contribute directly to production-grade code implementation for both frontend and backend systems using Python, JavaScript, and related technology stacks when technical progress or architectural clarity depends on engineering involvement - Operationalization and Knowledge Sharing: Codify successful deployment patterns, methodologies, and best practices into reusable tools, playbooks, and building blocks that scale across the organization and enable other engineers to execute deployments efficiently - Field Research and Feedback Loop: Gather production insights and behavioral data on LLM model performance, identify gaps where models underperform, synthesize customer feedback, and communicate findings to Research and Product teams to directly influence model improvements and product roadmap priorities - Cross-Functional Collaboration: Work collaboratively with Product, Research, Partnerships, Security, GRC, and GTM teams to align deployment strategy with company priorities, address compliance requirements, and drive customer success metrics that influence strategic direction - Stakeholder Communication and Leadership: Provide clear, concise communication to internal engineering teams, product stakeholders, and customer leadership; maintain team momentum through excellent follow-through, decisive action under pressure, and calm judgment when stakes are high ## Requirements ### education - {"name":"Bachelor's Degree in Computer Science or Related Field (Preferred)","description":"Formal education in computer science, software engineering, mathematics, physics, or equivalent practical engineering experience preferred but not strictly required; 5+ years of professional engineering experience can substitute"} ### technical - {"name":"Python Development","description":"Strong proficiency in Python for backend system development, data processing, and API implementation; ability to write clean, maintainable, and performant production code"} - {"name":"JavaScript/Full-Stack Web Development","description":"Solid experience with JavaScript, modern web frameworks, and full-stack development patterns for building user-facing applications that integrate AI capabilities"} - {"name":"LLM Integration and Prompt Engineering","description":"Technical understanding of large language model APIs, prompt design, fine-tuning considerations, context management, and techniques to optimize model output for production use cases"} - {"name":"System Design and Architecture","description":"Ability to design scalable, reliable distributed systems; experience with microservices, API design, authentication, caching, and production deployment patterns"} - {"name":"DevOps and Production Deployment","description":"Experience with containerization, cloud platforms, CI/CD pipelines, monitoring, logging, and operational best practices required to run systems reliably in production"} - {"name":"Generative AI Application Patterns","description":"Understanding of production patterns for AI applications including RAG (Retrieval-Augmented Generation), fine-tuning workflows, evaluation frameworks, and techniques for managing model uncertainty and hallucinations"} ### experience - {"name":"5+ Years Full-Stack Engineering Experience","description":"Demonstrated track record of 5 or more years building and shipping production software systems with substantial experience in customer-facing technical roles that required direct customer interaction and delivery accountability"} - {"name":"Complex Systems Delivery in Fast-Moving Environments","description":"Proven experience scoping, architecting, and delivering complex technical systems in fast-moving, ambiguous, or startup-like environments where requirements evolve and rapid adaptation is essential"} - {"name":"LLM and Generative AI Systems Experience","description":"Hands-on experience building, deploying, or operating systems powered by large language models or generative AI, with deep understanding of how model behavior, output quality, and inference characteristics directly impact product experience and user adoption"} - {"name":"Production-Grade Code Ownership","description":"Extensive experience writing, reviewing, and maintaining production-grade code across frontend and backend domains, with ability to drive technical excellence and architectural best practices"} ## Skills ### required - {"name":"Full-Stack Software Architecture","description":"Design and implement complete system architectures spanning frontend, backend, databases, and deployment infrastructure for production LLM-powered applications"} - {"name":"Large Language Model Systems","description":"Deep technical expertise in building production systems that leverage large language models, including API integration, prompt optimization, context management, and evaluation frameworks"} - {"name":"Python and Backend Development","description":"Professional-grade Python development for building scalable backend systems, APIs, and data processing pipelines"} - {"name":"Customer-Facing Technical Leadership","description":"Ability to partner directly with customer engineering teams, translate business requirements into technical solutions, and maintain accountability for production outcomes"} - {"name":"Rapid Decision-Making Under Ambiguity","description":"Skill in scoping work, making fast and sound technical decisions with incomplete information, and adjusting course while maintaining delivery momentum"} - {"name":"Production Systems Delivery","description":"End-to-end ownership of complex technical projects from design through stable production deployment with measurable business impact"} - {"name":"Stakeholder Communication","description":"Clear and effective communication with diverse audiences including customer stakeholders, engineers, product managers, and research teams"} ### preferred - {"name":"JavaScript and Modern Web Frameworks","description":"Experience with React, Vue, or other modern frontend frameworks for building user interfaces that integrate generative AI capabilities"} - {"name":"Cloud Platforms and DevOps","description":"Hands-on experience with AWS, GCP, or Azure for deploying, monitoring, and scaling production applications"} - {"name":"API Design and Integration","description":"Experience designing and consuming APIs at scale, including error handling, rate limiting, and integration patterns for third-party services"} - {"name":"Observability and Monitoring","description":"Proficiency with monitoring, logging, and observability tools (Datadog, Prometheus, etc.) for maintaining visibility into production system health"} - {"name":"Agile and Iterative Development","description":"Experience working in rapid iteration cycles with frequent customer feedback and ability to prioritize ruthlessly"} - {"name":"Security and Compliance","description":"Understanding of security best practices, compliance requirements (SOC 2, HIPAA, etc.), and secure software development practices"} - {"name":"Machine Learning Operations","description":"Familiarity with ML ops, model evaluation frameworks, A/B testing for AI systems, and techniques for managing model performance in production"} ## Tech stack ### tools - {"name":"Git and Version Control","description":"Professional version control practices and collaboration workflows"} - {"name":"Docker and Kubernetes","description":"Containerization and orchestration for deploying scalable production systems"} - {"name":"CI/CD Platforms","description":"GitHub Actions, GitLab CI, or Jenkins for automated testing and deployment pipelines"} - {"name":"Monitoring and Logging","description":"Observability tools like Datadog, ELK Stack, or CloudWatch for production system visibility"} - {"name":"OpenAI APIs","description":"Hands-on experience with GPT models, embeddings API, and other OpenAI platform capabilities"} ### others - {"name":"LLM Prompt Engineering","description":"Techniques for crafting effective prompts, few-shot learning, and chain-of-thought patterns to optimize model output"} - {"name":"RAG Architectures","description":"Retrieval-Augmented Generation patterns for combining LLMs with enterprise data sources"} - {"name":"Model Evaluation Frameworks","description":"Methods and tools for evaluating LLM output quality, safety, and reliability in production systems"} - {"name":"Generative AI System Design","description":"Architectural patterns for production-grade AI systems including error handling, fallbacks, and user feedback loops"} ### databases - {"name":"PostgreSQL","description":"Primary relational database for storing structured data and application state in production systems"} - {"name":"Vector Databases","description":"Specialized databases like Pinecone, Weaviate, or Milvus for implementing RAG and semantic search in LLM applications"} ### languages - {"name":"Python","description":"Primary backend language for LLM integration, API development, and data processing in production systems"} - {"name":"JavaScript/TypeScript","description":"Frontend and full-stack development for customer-facing applications that integrate generative AI capabilities"} ### frameworks - {"name":"React or Vue","description":"Modern frontend frameworks for building responsive user interfaces that leverage LLM capabilities"} - {"name":"FastAPI or Flask","description":"Python web frameworks for building scalable backend APIs that serve LLM requests"} - {"name":"Node.js/Express","description":"JavaScript runtime and framework for full-stack development and backend API services"} ## Benefits ### benefits - {"name":"Hybrid Work Flexibility","description":"Flexible hybrid work model requiring 3 days in office per week in Seattle headquarters, allowing remote work flexibility for 2 days"} - {"name":"Relocation Assistance","description":"Comprehensive relocation package to support employees relocating to Seattle from other locations"} - {"name":"Frontier AI Access","description":"Hands-on access to cutting-edge AI models and research breakthroughs from OpenAI, providing unique opportunity to work with state-of-the-art technology"} - {"name":"Strategic Customer Partnerships","description":"Direct partnerships with OpenAI's most strategic customers, providing high-impact projects and significant career visibility"} - {"name":"Cross-Functional Collaboration","description":"Opportunity to work directly with Research, Product, and GTM teams to influence AI model development and product direction"} - {"name":"Competitive Compensation","description":"Highly competitive salary and equity package typical of top-tier AI research organizations"} - {"name":"Professional Development","description":"Continuous learning opportunities and exposure to frontier AI technology through direct research collaboration and customer deployments"} - {"name":"Equal Opportunity Workplace","description":"Commitment to diversity, inclusion, and equal opportunity employment with reasonable accommodations for applicants with disabilities"} ## Compensation - **max:** 280000 - **min:** 180000 - **currency:** USD - **stockOptions:** true ## Interview process ### steps - {"name":"Initial Screening and Resume Review","description":"Ashby ATS screening of resume and background to verify alignment with 5+ years experience requirement, LLM deployment background, and full-stack engineering credentials"} - {"name":"Technical Phone Screen","description":"30-45 minute conversation with hiring manager or senior engineer covering system design approach, LLM integration experience, production deployment complexity, and decision-making under ambiguity"} - {"name":"Technical Deep Dive","description":"60-90 minute technical interview focused on a real-world deployment scenario; may include system design questions, code review exercise, or discussion of past project architecture decisions"} - {"name":"Customer Leadership Interview","description":"Interview with senior customer-facing team member to assess ability to embed with customers, communicate technical concepts to non-engineers, and drive adoption"} - {"name":"Product and Research Alignment","description":"Conversation with Product or Research team member to evaluate understanding of LLM capabilities, model behavior considerations, and ability to translate field feedback into product insights"} - {"name":"Final Round with Leadership","description":"Interview with hiring manager or team lead to assess overall fit, leadership potential, decision-making under pressure, and strategic thinking aligned with OpenAI's mission"} ## 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 Seattle. 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.