Lead Engineer
Total Performance Consulting
Lead Engineer
Total Performance Consulting
Governed AI and senior engineering services
A lab result can arrive on time and still be hard to use. It has to reach the right patient record, carry enough context for a physician to act on it, and make sense to the person receiving it. The same challenge applies to data from electronic health records, insurers, wearables, and medical devices.
We’re seeking a Lead Engineer, Health Data Integrations to build and operate the integrations behind a health data platform for personalized primary care. You’ll own the work from the first conversation with a lab, EHR vendor, or device partner through the point where a member or physician can use the data. You’ll work across APIs, data pipelines, mobile integrations, and front-end features on an API-first, event-driven Azure platform. The team uses Claude Code as its primary development interface.
This is a hands-on senior individual contributor role reporting to the Director of Engineering, Integrations. The role works directly with protected health information and external vendors and is open to candidates based in the United States who are authorized to work in the U.S.
The ideal candidate can sit down with a clinician or vendor, work out what data is available and how it will be used, and carry that integration into production. They can trace a result back to its source, explain a gap in plain language, and fix the underlying problem.
You should be able to carry an integration through the full arc:
Clinical Need → Partner Discovery → Integration Design → Data Validation → Production → Member and Physician Use
The work is complete when the right data reaches the right person in a form they can use.
Your partner for AI, consulting, software development, and nearshore staffing.
Governed AI and senior engineering services
Perform delivers governed AI and senior engineering services for mission-critical systems, combining consulting, staff augmentation, and AI delivery to implement AI, modernize legacy software, and assure quality for AI-powered products. Its Governed AI approach keeps AI transparent and auditable, with a human engineer accountable for every output, and its distributed team of about 100 engineers works in client time zones and integrates with existing teams. This differentiates it from competitors through explicit human accountability, long-term self-funding, and end-to-end services tailored to enterprise needs. Its goal is to enable safe, auditable, and dependable AI within enterprise workflows so organizations can adopt AI in critical operations without sacrificing reliability.
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