Senior Technical Product Engineer

Role overview A senior product-engineering seat on a small early-stage team building a data and specimen marketplace for health systems, labs, pharmaceutical, biotech, and AI customers. The role blends product ownership with hands-on engineering and serves as the primary technical voice across data infrastructure, agents, and applied AI.

Responsibilities - Make and review architecture decisions on a brokerage platform built with Python/FastAPI, TypeScript/React, Postgres, and Azure, partnering with a small group of business-minded engineers. - Own product and engineering work across the data pipeline covering specimen, slide, and clinical data intake, normalization, storage, validation, and customer response speed. - Act as product owner and engineer for the internal agent platform, including permissions, evaluations, cost controls, audit, and guardrails for sensitive data. - Ship features in buyer, supplier, and lab portals end-to-end, from problem definition to post-launch operation. - Spend time with lab and health-system partners to understand how data actually leaves their organizations, then translate those findings into shipped work.

Requirements - Track record as a reviewer of record on a production codebase, with examples of approving risky work and blocking popular work. - Architecture judgment that has prevented costly rewrites or steered teams away from bad design decisions. - Production software owned after launch, including on-call, incident response, and correcting data that turned out wrong. - Comfort beneath the application layer across ingest, queues, storage, migrations, and observability. - Practical agent and LLM engineering, including tool design, evaluations, failure modes, cost, and recognizing when an agent is the wrong answer. - Strong written communication, with examples of specs, RFCs, design docs, or postmortems that made messy problems precise.

Nice to have - Working knowledge of healthcare, life sciences, or lab operations, health data standards such as HL7, FHIR, or DICOM, medical coding, revenue cycle, or regulated-environment experience. - Design chops for product surfaces and internal tools.

Benefits and work setup - Early-stage team that uses AI-native tooling daily, including internal coding assistants, and expects clear-eyed judgment about where those tools produce low-quality output.