Translucent AI provides an agentic AI platform that delivers real-time financial visibility and root-cause analysis for hospitals and health systems.
<h2><strong>Why Translucent</strong></h2> <p>Healthcare providers drive $2.5 trillion in medical expenditures annually — and operate on razor-thin 2–5% margins. Despite these stakes, the finance teams behind these organizations are buried in spreadsheets, manual data pulls, and disconnected systems, spending more time finding and cleaning data than actually using it to make decisions.</p> <p>Translucent is changing that. We're building the agentic AI platform designed exclusively for healthcare finance— giving every finance team, department, service line their own arsenal of AI Agents that run 24/7, understand their specific data, business logic, and workflows.</p> <p>Founded in 2024 and backed by GV, NEA, FPV, and Virtue, we've already been deployed by healthcare organizations managing over $5 billion in combined revenue. The product-market fit is real, the problem is massive, and we're just getting started. If you want to work at the intersection of AI and one of the most complex, consequential industries in the world — this is the place.</p> <h3>About the role</h3> <p>We’re hiring a Senior Forward Deployed Engineer with a data engineering focus to join our team in New York. You will sit at the intersection of our customers' financial and clinical data and the agentic AI systems we are building on top of it. You will build and maintain the data integration interfaces, pipelines, and semantic layers that make healthcare data legible to our products, and you will partner closely with platform engineers to keep our core data systems fast, correct, and well-tested.</p> <p>This is a high-ownership role. You will work directly with customers to understand their source-of-truth financial and clinical models, then translate that understanding into durable, well-modeled data systems.</p> <h3>What you'll do</h3> <ul> <li>Build and maintain abstracted data integration interfaces for healthcare data.</li> <li>Capture and understand the source-of-truth financial and clinical record models used by our customers. Potentially go on-site with customers to capture business logic.</li> <li>Optimize data ingestion and transformation pipelines for correctness, performance, and cost.</li> <li>Build semantic understanding into our core data systems so they can power agentic AI workflows.</li> <li>Partner with platform engineers to build and maintain the core data systems our products depend on.</li> <li>Validate data pipeline correctness and build rigor into our integration test suites at every opportunity.</li> </ul> <h2><strong>What we're looking for</strong></h2> <h3><strong>Must-haves</strong></h3> <ul> <li>Strong SQL optimization experience in a columnar data warehouse (BigQuery, Snowflake, Redshift, or similar), or Databricks.</li> <li>Strong Python skills, including hands-on experience with pandas (must have) and the broader scientific Python ecosystem. Strong preference to use types where possible, we use pydantic liberally. DBT experience preferred.</li> <li>Strong grounding in the fundamentals of computation, logic, and algorithms.</li> <li>Solid data modeling instincts: comfortable designing schemas, reasoning about normalization vs. denormalization, and modeling complex domain entities.</li> <li>Experience with orchestration tools (<em>e.g.</em> Prefect, Airflow, Dagster, Fivetran, Airbyte) etc.</li> <li>3-5+ years of post-university industry experience</li> </ul> <h3><strong>Nice-to-haves</strong></h3> <ul> <li>Hands-on experience with GCP (BigQuery, GCS, Spanner, IAM, etc.).</li> <li>Prior exposure to healthcare data (claims, EHR, financial systems) or other regulated/complex domains.</li> <li>Experience working directly with customers or stakeholders in a forward-deployed, integrations, or solutions engineering capacity.</li> <li>Golang experience.</li> </ul> <h3><strong>Education</strong></h3> <p>Bachelor's degree (or higher) in a quantitative discipline: computer science, mathematics, statistics, physical or life sciences, engineering.</p> <h3><strong>Location</strong></h3> <p>Union Square, New York City.<strong> In-office 4 days per week.</strong></p> <p>Anticipated compensation: $200,000 - $250,000 with Equity</p>