T

Total Performance Consulting

Governed AI and senior engineering services

Lead Engineer - Health Data Integrations

Full-Stack EngineeringUpdated on Nov 5
Full-timeUnited StatesNo salary listed

About the Job

Requirements

  • A bachelor's degree in computer science or a related field and 8+ years shipping software, including 3+ years building healthcare data integrations at a health-tech, digital health, or healthcare startup.
  • Hands-on production experience with FHIR R4 and SMART on FHIR, plus working knowledge of HL7 v2, C-CDA, and clinical terminologies such as LOINC and SNOMED CT.
  • Integration experience in at least two areas: hospital and EHR systems; payer data such as eligibility, claims, or X12 EDI; and lab systems.
  • Experience integrating Apple HealthKit or Android Health Connect, including the native or cross-platform mobile work involved, and working with wearable APIs such as WHOOP, Fitbit, Oura, or Garmin.
  • Experience leading a substantial platform build or integration program end to end.
  • Full-stack development experience with a modern back end such as Node.js, .NET, or Python and a front end such as React or Next.js, including production experience building APIs, event-driven systems, and data pipelines.
  • Cloud-native experience on Azure, or equivalent experience on another cloud platform and willingness to work in Azure, including CI/CD and infrastructure as code.
  • Practical experience applying HIPAA requirements and protecting protected health information in production systems.
  • Daily use of AI coding tools such as Claude Code or Copilot, with a clear approach to reviewing and testing their output.
  • Ability to work independently on a small team, raise blockers early, and communicate clearly with engineers, clinicians, and vendor partners.
  • Must be based in the United States and authorized to work in the U.S.

Responsibilities

  • Build and operate integrations with lab and diagnostics partners so results arrive complete, normalized, and ready for members and physicians to use.
  • Connect EMR and EHR systems using FHIR and legacy interfaces where needed, and integrate payer data, including eligibility, claims, and patient-access APIs.
  • Integrate on-device mobile health data and cloud-based wearable APIs, handling consent, synchronization, and gaps in device data.
  • Lead the work to bring data from in-clinic medical devices into the cloud platform.
  • Map data from different sources into a common model that supports standard clinical terminology, patient matching, provenance, and auditability.
  • Build APIs, services, and front-end features that help members understand their health data and physicians act on it.
  • Work directly with labs, EHR vendors, payers, and device partners to scope, test, and launch integrations; partner with product, clinical, and data engineering teams to decide which data matters and how to present it.
  • Design for HIPAA requirements from the start by building in encryption, access controls, audit logging, and minimum-necessary data handling, and align vendor integrations with Business Associate Agreements.
  • Set standards for testing, observability, and CI/CD so the team can catch integration failures before they affect members or physicians.
  • Use Claude Code and agentic development in the daily workflow, from prototyping and code generation through automated testing and deployment, and define how the team reviews and verifies AI-generated changes.
  • Work with technical and business product owners to test assumptions, clarify what each integration needs to deliver, and sequence work by impact.

About the Company

Total Performance Consulting

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.

Company size
51-200
Company stage
Not listed
Total funding
Not listed
Headquarters
Atlanta, GA
Founded
2005

Recently Posted Jobs

Explore more opportunities at Total Performance Consulting

See more jobs