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Salary: USD 180,000 - 230,000 / annual
Translucent is an agentic AI platform built exclusively for healthcare finance, founded in 2024 and backed by GV, NEA, FPV, and Virtue. The company is deployed by healthcare organizations managing over $5 billion in combined revenue, solving a critical problem: healthcare finance teams spend more time finding and cleaning data than making decisions.
As a Forward Deployed Insights Engineer, you will sit at the intersection of customer healthcare finance problems and the agentic AI/ML systems built to solve them. You'll work on top of a unified data ontology maintained by Analytics Engineers and agent infrastructure built by the AI Engineering team, focusing on building solutions for specific customer problems rather than underlying frameworks.
Key responsibilities include: configuring customer workspaces and building new AI agents and ML models on existing infrastructure; working directly with customers and product teams to scope high-value solutions in healthcare finance; configuring visualizations and presentation layers that turn model outputs into actionable insights for finance and operations leaders; presenting and demoing ML/AI solutions to end users to build trust; partnering with product to generalize customer-specific solutions into reusable platform features; and validating correctness and reliability of agents and models through rigorous testing.
This is a high-ownership, customer-facing role requiring deep healthcare domain experience (consulting, forward-deployed, or health tech background with exposure to claims, EHR, or financial/revenue cycle data). You must have strong Python and SQL skills, real hands-on experience with AI-assisted coding tools (Cursor, Claude Code), exposure to AI/ML projects or agentic systems, comfort building visualizations or front-end presentation layers (dashboards, BI tools, lightweight frameworks), and experience working directly with end users presenting technical solutions to non-technical stakeholders. Strong version control and GitOps workflow experience is essential—you'll own changes through code review and ship via automated CI/CD.
Nice-to-haves include GCP experience and experience productizing bespoke customer solutions into reusable platform features. A Bachelor's degree in computer science, data science, statistics, mathematics, or related quantitative field is required, or equivalent experience building and deploying applied ML/AI solutions. Advanced degrees are a plus but hands-on AI/ML build experience and healthcare domain exposure are weighted more heavily.
