Forward Deployed Insights Engineer (Applied AI)

About the job Forward Deployed Insights Engineer (Applied AI) Forward Deployed Insights Engineer (Applied AI) Company: Translucent 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 Translucent Translucent is building an agentic AI platform for healthcare finance, helping health systems manage complex financial data and workflows and turn it into decisions leaders trust. It is already deployed at organizations managing over $5B in combined revenue. Founded in 2024, Translucent has about 27 people in New York and has raised $34M from GV, NEA, FPV and Virtue. The Role Translucent 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 Transparent Search Group