Forward Deployed Engineer (AI Infra)

Location: San Francisco, United States; hybrid work with 3 days in the office per week; travel up to 50% required.

Salary: $185,000–$300,000 base pay annually, plus equity and potential performance-related bonuses.

Company

OpenAI is an AI research and deployment company developing general-purpose artificial intelligence and products intended to benefit humanity.

What you will do

• Own technical delivery for semiconductor and AI-infrastructure workstreams from scoping and prototypes through validation, production deployment, and adoption.
• Work with customer engineers, researchers, product engineers, and stakeholders to define workflows, workloads, baselines, constraints, and success criteria.
• Build and debug production-quality software, including harnesses, integrations, and product features for chip design, verification, inference, and performance engineering.
• Design reproducible experiments, evaluations, graders, and benchmarks to validate correctness and performance on real workloads and hardware.
• Investigate model behavior and failure modes, contributing evaluation or training data and targeted experiments to improve model capabilities.
• Turn successful approaches into reusable software, tools, playbooks, and product improvements while maintaining alignment, ownership, risks, and next steps.

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 LLMs or generative models, with an understanding of how model behavior affects product experience.
• Ability to simplify complexity, make sound decisions under pressure, communicate clearly with engineers, product teams, and customer stakeholders, and identify risks early.
• 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.

Nice to have

• Experience in semiconductor development, data-center systems, or inference engineering.

Culture & Benefits

• Hybrid work model with relocation assistance for eligible employees.
• Medical, dental, and vision insurance, with employer contributions to Health Savings Accounts.
• 401(k) retirement plan with employer match, paid parental and medical leave, paid time off, company holidays, and paid sick or safe time.
• Mental health and wellness support, life and disability coverage, and an annual learning and development stipend.
• Daily office meals, eligible meal delivery credits, commuter benefits, charitable donation matching, and wellness stipends.

Hiring process

• More details about benefits and role conditions are provided during the hiring process.
• Background checks are administered in accordance with applicable law for US-based candidates.