Forward Deployed Engineer (FDE) - AI Infra - San Francisco

Details

OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. The team operates at the intersection of customer delivery and core platform development.

Forward Deployed Engineers lead complex deployments of frontier models in production, embedding with customers where model performance matters, delivery is urgent, and ambiguity is the default. The role involves mapping customer problems, structuring delivery, and shipping quickly.

As a Forward Deployed Engineer for AI Infra, you will work directly with customer engineers, researchers, and product engineers on optimization problems across semiconductors and AI infrastructure. You will write and debug software, run experiments against real workloads and hardware, and improve the tools and products used across engagements.

Work may include inference performance and chip-design optimization. You will define problems and success criteria, build software to test approaches, and support work through validation and deployment. Success means producing results that meet correctness and performance requirements while contributing improvements that can be reused across engagements.

The role is based in San Francisco and follows a hybrid work model requiring three days in the office per week. Travel of up to 50% is required.

Responsibilities

• Own technical delivery for semiconductor and AI-infrastructure workstreams, from initial scoping and prototypes through validation, production deployment, and adoption.
• Work closely with customer engineers to understand workflows and constraints, define workloads, establish baselines and success criteria, and help integrate delivered solutions into customer processes.
• Scope and sequence delivery, identify dependencies and blockers early, and make practical trade-offs between scope, speed, and quality.
• Build and debug production-quality software, including harnesses, integrations, and product features that apply frontier models to chip design, verification, inference, and performance engineering.
• Design reproducible experiments, evaluations, graders, and benchmarks to test approaches, validate correctness and performance, and determine whether improvements hold up in real engineering environments.
• Investigate model behavior and failure modes alongside researchers, contributing evaluation or training data and targeted experiments where they can improve underlying capabilities.
• Contribute directly to core product development by resolving tooling gaps, shipping useful improvements, and bringing field learning into product decisions.
• Lead technical discussions and maintain alignment across customer, Product, and Research teams.
• Build the domain and product fluency needed to explain capabilities, limitations, and results while keeping ownership, risks, and next steps clear.
• Turn successful approaches into reusable software, tools, and playbooks that reduce effort for future engagements and help customer teams operate delivered systems.

Requirements

• 5+ years of engineering or technical deployment experience, including customer-facing work.
• Experience scoping and delivering complex systems in fast-moving or ambiguous environments.
• Ability to write and review production-grade software and debug unfamiliar systems across code, integrations, and runtime behavior.
• Experience building or deploying systems powered by large language models or generative models, with an understanding of how model behavior affects product experience.
• Ability to simplify complexity and make fast, sound decisions under pressure.
• Clear communication skills when working with engineers, product teams, and customer stakeholders.
• Ability to identify risks early and adjust without slowing down.
• Strong judgment and composure in high-stakes situations.
• Strong product sense and experience contributing to productization efforts.
• Hands-on experience with applied machine learning, model evaluation, data quality, experimentation, or model-behavior analysis.
• Ability to turn ambiguous technical problems into clear evaluations, credible baselines, and reproducible experiments.
• Comfort learning unfamiliar technical domains and working closely with researchers, product engineers, and customer engineers.
• Experience in semiconductor development, data-center systems, or inference engineering is helpful.

Benefits

• Base salary of $185,000–$300,000 per year, plus equity.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses.
• 401(k) retirement plan with employer match.
• Paid parental leave, medical leave, and caregiver leave.
• Paid time off, company holidays, office closures, and paid sick or safe time as required by applicable law.
• Mental health and wellness support.
• Employer-paid basic life and disability coverage.
• Annual learning and development stipend.
• Daily office meals and eligible meal delivery credits.
• Relocation support for eligible employees.
• Additional benefits may include charitable donation matching and wellness stipends.

OpenAI is an equal opportunity employer committed to providing reasonable accommodations to applicants with disabilities. Background checks are administered in accordance with applicable law.