The role
- COMP
- $190K - $235K
- EQUITY
- Competitive equity
- LOCATION
- New York
- WORKPLACE
- On-site
- EXPERIENCE
- 3 - 5 years
- VISA
- None
- STACK
- Python, FastAPI, TypeScript, JavaScript, REST API, Docker, Kubernetes, AWS, GCP
- INDUSTRY
- AI, Devtools
/roles — ROLE_434
Forward Deployed Engineer
Early-stage AI infrastructure lab giving agents persistent memory and deep models of their users
The company
Research-driven AI lab building identity and memory infrastructure that lets AI apps and agents learn rich, evolving models of their users, powered by its own trained models.
- STAGE
- Series A-stage
- FUNDING
- $9M raised
- TEAM
- ~15 people
- FOUNDED
- 2023
- BACKING
- VC-backed
JD — the work
About the role
You would manage relationships with enterprise customers from pre-sales demos through post-sales integration for the company's memory and identity product. This is the first dedicated forward deployed hire at a fast-growing AI lab that builds and trains proprietary models and has seen rapid growth in developer adoption. The role mixes deal management, technical demos, and hands-on integration work inside customer codebases, all on site in New York.
What you'll do
- Run the enterprise deal process: sort incoming leads, keep opportunities moving, and follow through on promises
- Create demos, decks, one-pagers, and sample integrations customized for each customer's industry and use case
- After a deal closes, work inside customer codebases to review them and write the integration yourself
- Coach enterprise teams on how to think about building with agents and how to use the product well
- Bring pain points and lessons from customers back to engineering to shape the roadmap
What they're looking for
- 3 to 5 years of engineering experience with meaningful customer-facing work
- Solid Python and TypeScript, plus REST APIs, FastAPI, Docker, Kubernetes, and AWS or GCP
- Ability to run technical demos and guide enterprise deals from first contact to close
- Comfort reading unfamiliar codebases and building integrations inside them
- Understanding of how agentic AI applications are built