OpenAI Forward Deployed Engineer at OpenAI responsible for leading complex deployments of frontier AI models in production. This role involves working directly with customers to optimize semiconductor and AI infrastructure workflows.
Responsibilities
Forward Deployed Engineers lead complex deployments of frontier models in production. You will embed with customers where model performance matters, delivery is urgent, and ambiguity is the default. You will use this to map their problems, structure delivery, and ship fast.
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 product used across engagements.
Success in this role means owning the delivery state across workstreams. You will hold the bar on quality and pace and help OpenAI learn through execution.
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.
Own technical delivery for agreed semiconductor and AI-infrastructure workstreams, from initial scoping and prototypes through validation, production deployment and adoption.
Work closely with customer engineers to understand their workflows and constraints, define workloads, baselines and success criteria, and help what you build become part of how they work.
Scope and sequence delivery, identify dependencies and blockers early, and make practical trade-offs between scope, speed and quality as the work develops.
Personally build and debug production-quality software, including harnesses, integrations and product features that apply frontier models to problems in chip design, verification, inference and performance engineering.
Design reproducible experiments, evaluations, graders and benchmarks to test approaches, validate correctness and performance, and establish 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 the underlying capability.
Contribute directly to core product development, working with product engineers to resolve tooling gaps, ship useful improvements and bring field learning into product decisions.
Lead technical discussions and maintain alignment across customer, Product and Research teams. Build the domain and product fluency to explain capabilities, limitations and results, and keep ownership, risks and next steps clear.
