Forward Deployed Insights Engineer (Applied AI)

Company: Confidential - Series A healthcare-finance AI company
Location: New York, NY (Union Square office, 4 days in person)
Compensation: $180,000 - $230,000 + competitive equity
Employment Type: Full-time
Visa Sponsorship: Not available (US citizens and green card holders)

About the Company

A Series A company building an agentic AI platform for healthcare finance, already deployed at health systems managing billions in combined revenue, with a team of about 30 in New York.

The Role

Our client is hiring a Forward Deployed Insights Engineer to sit at the intersection of customer healthcare finance problems and the AI that solves them. Analytics Engineers get the data in accurately; this role builds on top of it: the context layer agents operate on, tailored agents and predictive models for each customer, and the iteration that turns outputs into decisions. This is applied data science, not full stack, platform engineering or dashboards. You will work in Python with the company's agent harnesses and eval tooling, partnered with the value team and directly with health system finance leaders.

What You Will Do

• Build tailored agents and ML models for each customer on existing agent infrastructure.
• Own the customer context layer that agents, including platform-level agents, operate on.
• Validate outputs with harnesses and evals so agents and models are accurate enough to earn trust.
• Iterate on insights and presentation with the value team until customers act on them.
• Scope problems with end users and present solutions to finance and operations leaders.

What You Bring

• 3-10 years of data science, applied ML or analytics work
• Shipped applied ML, predictive models or AI agents to production for a customer, owned end to end
• Hands-on healthcare experience (data, workflows or products); healthcare finance strongly preferred
• Hands-on LLM and agentic tooling: building and evaluating agents in real work
• Strong hands-on Python and SQL
• Customer-facing technical work (forward deployed or implementation)
• Bachelor's in a quantitative field or equivalent applied ML work
• Ability to work in the New York office 4 days a week

Nice to Have

• Pipelines, distributed compute or cloud (Snowflake, Databricks, Spark)
• CI/CD and git workflow ownership

Interview Process

Intro call (30 min), technical screen on data transformation and pipelines (45 min), onsite case and culture session (2-3 hours), meet the founders (30 min).

Tech Stack

Python, SQL, LLMs, agentic AI, evals, data visualization