Forward Deployed Engineer (FDE), Legal-SF
HotApplication analysis
Forward Deployed Engineer (FDE), Legal-SF at OpenAI is a forward deployed ai research lab role for engineers who want customer-facing technical work with real deployment ownership.
Reading this role
This Forward Deployed Engineer role centers on embedded customer delivery — discovery, prototyping, integration, and production rollout. Key signals from the listing: Senior scope.
About OpenAI
OpenAI ships frontier models to real customers through small, high-trust engineering teams. Forward deployed roles sit between product, research, and enterprise buyers. The role is anchored in New York City, so expect on-site customer work in that region.
Signals in the listing
Stand out for Forward Deployed Engineer (FDE), Legal-SF
- Lead your application with one paragraph tying Forward Deployed Engineer (FDE), Legal-SF to a specific customer or deployment you owned — OpenAI hires for shipped outcomes, not tool lists.
- Prepare a 5-minute “week one on site” plan: who you would meet, what you would inspect in their stack, and what artifact you would deliver by day five.
- Show you can go from discovery notes → working integration → production checklist without needing a large internal team.
- This role is tied to New York City — mention willingness to work on-site with customers and any existing ties to that market (clients, partners, or domain knowledge).
Stand out at OpenAI
- Demonstrate customer obsession with safety constraints with a concrete example — OpenAI will probe for specifics, not buzzwords.
- Demonstrate writing and communication with a concrete example — OpenAI will probe for specifics, not buzzwords.
- Interview loops emphasize problem decomposition, taste in product, and whether you can earn trust with technical and non-technical stakeholders quickly.
- Read recent engineering blog posts, product launches, and customer stories on openai.com — reference one explicitly in your outreach to show genuine interest.
Tailored from this listing’s title, company, and description. Always verify requirements on the company careers page before applying.
Role description
ABOUT THE TEAM OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We embed deeply with users to solve high-leverage problems. We move quickly from prototype to deployment and surface patterns that shape the platform. We operate at the intersection of customer delivery and core development. We work closely with Product, Research, and Go-To-Market (GTM). ABOUT THE ROLE We are hiring a Forward Deployed Engineer (FDE) to build and deploy AI systems for legal work. You will embed deeply with customers—often working closely with senior legal practitioners—to identify the right first use case, rapidly prototype a solution, and prove measurable value. Early engagements may focus on creating a “hero” workflow that shows how OpenAI’s models can support legal analysis, drafting, research, or real-time work with complex case records. You will own the technical work from discovery and proof of concept through production adoption, while translating customer workflows and constraints into clear product feedback. As the motion matures, you will turn successful deployments into repeatable patterns that can scale across larger accounts and the broader legal market. This role is based in San Francisco or New York City. We use a hybrid work model of three days in the office per week and offer relocation assistance. Travel up to 50% may be required. IN THIS ROLE, YOU WILL - Embed with law firms and legal teams to understand their workflows, identify high-value opportunities, and select the right initial use cases to prove value. - 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 - 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 build