Technical Implementation Program Manager

Bunkerhill Health Inc.
San Francisco, CA, United States
10 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
3 years minimum
Working hours
Regular working hours
Job source

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Integrity Interoperability OAuth SQL Databases Fast Healthcare Interoperability Resources Health Level Seven International Epic Clarity

Job description

You’d be the second person on our implementations team, working directly with David Wen, VP of Implementations, who spent four years at Epic before joining Bunkerhill. Together you’ll decide how Bunkerhill takes AI from signed contract to live clinical workflow, at 5 to 10 health systems at a time.

You’ll design the technical approach for each use case, build it with our engineers and customer IT, and take it through go-live yourself: in the interfaces, the data and the auth flows. If you’ve done EHR implementations and wanted your work to reach patients faster, this is that job., You’ll own each customer’s lifecycle across multiple use cases at once, from first workflow conversation to stable production.

  1. Discovery and architecture. Map the clinical workflow, data sources, triggers and required writebacks, then design and defend the technical approach and scope.
  2. Ingestion. Guide customer teams to stand up cohort feeds and triggers through SQL extracts (such as Epic Clarity), HL7 v2 feeds or Bulk FHIR.
  3. Data integrity. Validate the end-to-end flow yourself: sample, reconcile against Epic and ancillary systems, chase edge cases and set up monitoring.
  4. Runtime setup. Install and configure the Epic on FHIR app (OAuth2 background user, security points, app registration), and guide SMART on FHIR setups where they fit.
  5. Writebacks. Choose and implement the right writeback channel for each use case: FHIR create APIs, HL7 Z-segments, portal APIs or SMART workflows.
  6. Delivery. Build and run the plan, manage risks and dependencies, and drive our engineers and customer IT to deadlines through go-live and hypercare.
  7. Repeatability. Turn what works into frameworks our engineering team can reuse, so the next use case ships faster than the last.

Requirements

You’ve built healthcare integrations yourself, not just managed the people who did. You probably have 3+ years of implementation or integration work at a health system, an EHR vendor, or a healthtech company.

  • You’ve worked inside an EHR in production. 3+ years of implementation or integration work at a health system, an EHR vendor, or a healthtech company.
  • You know interoperability well. You’ve used HL7 v2, FHIR R4, OAuth2 and app registration on real projects, and when an interface stops working, you know where to look.
  • You check data before you trust it. You’ve set up feeds through SQL extracts like Epic Clarity, HL7 or Bulk FHIR, and you’ve run or directed the sampling and reconciliation that showed the data was right.
  • You get results back to clinicians. You’ve written results into an EHR or clinical system using FHIR create APIs, Z-segments or portal APIs, so the output appears where clinicians already work.
  • You own outcomes, not tasks. You’ve taken an implementation from discovery through hypercare, and when the spec is unclear, you make the call instead of waiting for one.
  • You’d rather build the playbook than follow one. You want startup speed and ownership, and you’re comfortable running several health systems at once.

About the company

About Bunkerhill

Health systems generate enormous amounts of data every day. We turn that data into action so that clinicians can focus on patients, workflows run seamlessly, and care reaches the people who need it most.

Today our agentic AI platform, Carebricks, is live at 15 health systems, including Cleveland Clinic, Mayo Clinic, Intermountain Health and UTMB. Hospitals bring us the problems their teams already know need fixing, and we turn them into AI agents that run inside real clinical workflows. At one health system, nephrology wait times dropped by more than half. At another, urgent lung follow-ups are handled 80% faster.

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