The role
- COMP
- $180K - $250K
- EQUITY
- Competitive equity
- LOCATION
- New York
- WORKPLACE
- On-site
- EXPERIENCE
- 2 - 5 years
- VISA
- None, Visa transfers
- STACK
- Python
- INDUSTRY
- AI, B2B, Data, Enterprise
/roles — ROLE_386
Founding Forward Deployed Engineer
Early-stage AI company helping B2B enterprises find and act on expansion revenue in existing accounts
The company
An early-stage enterprise software company combining LLMs with customer data to show B2B teams which accounts to focus on after the sale and how to grow them.
- STAGE
- Series A-stage
- FUNDING
- $10M+ raised
- TEAM
- founding team of <10
- FOUNDED
- 2025
JD — the work
About the role
You would own how the company's AI revenue platform gets deployed inside enterprise customers, bridging disorganized data warehouses and agent workflows running in production. A big part of the job is capturing business knowledge that lives in people's heads and encoding it as validated data models that drive automated account expansion. Expect about 20 to 30% of your time with customers and the rest on focused data work. You would join early, on a small team that has already won meaningful contract revenue and is backed by well-known venture investors.
What you'll do
- Bring customers live: secure data access, make sense of undocumented warehouses, and tie schemas to churn, expansion, and ARR
- Interview customer stakeholders, settle clashing definitions of key metrics, and encode the answers as tested SQL in a semantic layer
- Roll out agent workflows in each customer's environment and confirm they move revenue numbers measurably
- Juggle two or three customer engagements at once, working in shared channels with their engineers and data owners
- Be a daily user of the in-house agent tools and tell engineering what would strengthen evals, guardrails, and validation
What they're looking for
- 2 to 5 years of hands-on technical experience
- Strong SQL and Python, and comfort exploring unfamiliar data warehouses
- Skill at interviewing business stakeholders and turning fuzzy definitions into precise logic
- Readiness to work on-site in New York