Forward Deployed Engineer (FDE) - SF
Forward Deployed Engineer · Senior · Full Time
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Role
What you'll do.
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.
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.
Qualifications
What we look for.
Technical
Production-Grade Full-Stack Development
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.
Large Language Model Systems Experience
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.
Complex Systems Architecture
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.
API Integration and System Integration
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.
Education
Computer Science or Related Field
Bachelor's degree in Computer Science, Software Engineering, or related technical discipline preferred. Equivalent professional experience demonstrating depth in software engineering fundamentals is valued.
Systems Design Knowledge
Strong foundational knowledge of distributed systems concepts, scalability, performance optimization, and production architecture patterns. Self-directed learning in AI/ML systems architecture is advantageous.
Experience
Senior Engineering Experience
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.
Customer-Facing Technical Roles
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.
Fast-Paced, Ambiguous Environments
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.
Production Incident Response and Resilience
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
Python Development
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.
JavaScript/TypeScript
Proficiency in JavaScript or TypeScript for full-stack development, including modern frontend frameworks and backend runtime environments like Node.js.
System Design and Architecture
Ability to design scalable, maintainable systems that meet both technical requirements and business constraints. Experience making architectural trade-offs and documenting design decisions.
Customer Collaboration and Communication
Excellent communication skills across technical and non-technical audiences. Ability to gather requirements, explain complex technical concepts clearly, and build trust with external stakeholders.
Project Scoping and Execution
Skill in breaking down complex projects into manageable components, sequencing delivery, estimating effort, and managing scope creep while protecting quality.
Decision-Making Under Pressure
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.
LLM Application Development
Direct experience building applications powered by large language models, understanding model APIs, prompt engineering, retrieval-augmented generation, and integration patterns.
Preferred
Kubernetes and Container Orchestration
Nice to haveExperience with Kubernetes, Docker, or other container orchestration platforms for managing production deployments at scale.
Cloud Platform Experience
Nice to haveFamiliarity with major cloud platforms such as AWS, Google Cloud, or Azure, including deployment, scaling, and infrastructure management practices.
Observability and Monitoring
Nice to haveExperience designing and implementing monitoring, logging, and observability solutions for production systems. Knowledge of tools like Prometheus, Datadog, or ELK stack.
API Design and Development
Nice to haveExpertise designing RESTful or gRPC APIs, understanding versioning strategies, backward compatibility, and API documentation best practices.
Database Design and Optimization
Nice to haveExperience designing database schemas, optimizing queries, and choosing appropriate database technologies for different use cases (SQL, NoSQL, vector databases).
Security and Compliance
Nice to haveUnderstanding of application security principles, data protection, authentication/authorization patterns, and compliance requirements relevant to enterprise deployments.
Machine Learning Operations (MLOps)
Nice to haveExposure to MLOps practices including model versioning, deployment pipelines, A/B testing frameworks, and monitoring model performance in production.
Generative AI Ecosystem Knowledge
Nice to haveFamiliarity with the broader generative AI ecosystem including fine-tuning approaches, prompt engineering frameworks, vector databases, and emerging AI application patterns.
Tech stack
Languages
Frameworks
Databases
Tools
Other
Compensation
Pay and benefits.
Base·USD 185,000 – 300,000
Equity·Stock options
Benefits
Equity and Stock Options
Significant equity package aligned with OpenAI's mission and growth trajectory, providing long-term wealth creation opportunity.
Health Insurance Coverage
Comprehensive medical, dental, and vision insurance plans with employer contributions for the candidate and eligible dependents.
Mental Health and Wellness Programs
Access to mental health services, wellness platforms, fitness programs, and counseling resources supporting employee well-being.
Retirement Planning
401(k) matching program with employer contributions to support long-term retirement savings and financial security.
Paid Time Off and Vacation
Generous paid vacation, sick leave, and personal days allowing for work-life balance and family time.
Relocation Assistance
Full relocation package including moving expenses, temporary housing, and career transition support for new hires relocating to San Francisco.
Professional Development
Learning and development budget for conferences, courses, and skill enhancement programs to support career growth.
Parental Leave
Comprehensive parental leave policies supporting both mothers and fathers with paid time following the birth or adoption of a child.
Process
Interview steps.
- 01
Recruiter Screening
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.
- 02
Technical Phone Interview
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.
- 03
System Design Assessment
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.
- 04
Customer Collaboration and Communication
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.
- 05
Case Study or Real-World Problem
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.
- 06
Interview with Leadership
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 posting
Original listing.
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.
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. 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.
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