Forward Deployed Engineer (FDE), Legal-SF
The Forward Deployed Engineer will partner with legal industry customers to build, prototype, and deploy AI-powered systems using OpenAI's models. This role involves embedding with clients to solve complex workflows and translating field feedback into scalable product improvements.
- Compensation
- $185K–$300K / yr
- Location
- New York City
- Work setup
- Hybrid
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Solutions engineering
- Posted
Skills
Must have
- 5+ years of software engineering, ML engineering, or technical deployment experience
- Experience with customer-facing ownership in financial services or adjacent regulated industries
- Experience owning complex AI or data-driven systems end-to-end
- Proficiency in writing and reviewing production-grade code using Python, JavaScript, or comparable stacks
- Experience deploying systems powered by LLMs or generative models
Nice to have
- Experience with legal technology, legal services, compliance-heavy workflows, or professional services
Full 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 building blocks that others can use
- Share field feedback that helps Research and Product understand where the models succeed and where they can improve
You might thrive in this role if you
- Bring 5+ years of software engineering, ML engineering, or technical deployment experience with customer-facing ownership in financial services or adjacent regulated industries.
- Have experience with legal technology, legal services, compliance-heavy workflows, or professional services; this is helpful but not required.
- Have owned complex AI or data-driven systems end-to-end, from scoping through production adoption, in environments where errors carry real financial or regulatory consequences.