Healthcare software engineering

Engineering services for healthcare, interoperability and AI.

I help teams design and build software where clinical workflows, reliable data exchange and evolving product requirements need to work together.

How I can help

Systems that stay understandable as they grow.

The work starts with the system boundary: what moves between people, services and clinical contexts—and what must remain explicit.

How I can help

HealthTech Product Engineering

A healthcare product needs more than a frontend and an API. It needs clear domain boundaries, predictable data flows, controlled access and a backend that can evolve with clinical requirements.

Typical challenges

  • A clinical workflow is manual or fragmented.
  • An MVP needs a foundation that can be extended.
  • The boundary between frontend, API and data is unclear.

What I can build

  • Patient-facing applications and care workflows
  • Clinical dashboards and internal tools
  • APIs, authentication and data models

Typical deliverables

  • Healthcare MVP
  • Backend API and API documentation
  • Clinical frontend
  • Database and deployment architecture

Relevant technologiesPython · FastAPI · React · TypeScript · PostgreSQL · Docker

How I can help

Healthcare Interoperability

Clinical data only becomes useful across systems when identifiers, context and meaning travel with it. I design integration paths that make those contracts reviewable.

Typical challenges

  • An existing system needs to speak FHIR.
  • A legacy feed delivers HL7 v2 messages.
  • Patients, encounters and local codes do not map consistently.

What I can build

  • FHIR API design and resource modeling
  • HL7 v2 → FHIR adapters
  • Integration boundaries, identifier strategies and mapping concepts

Typical deliverables

  • FHIR API design
  • FHIR resource model
  • HL7 v2 → FHIR adapter
  • Integration documentation and mapping rules

Relevant technologiesFHIR R4 · HL7 v2 · HAPI FHIR · Python · FastAPI · Pydantic

How I can help

Clinical AI Engineering

I prototype AI-assisted healthcare workflows with structured outputs, source traceability and a clear human review step. This is engineering work—not medical advice or autonomous clinical decision-making.

Typical challenges

  • Clinical text needs to become usable structured data.
  • Model output needs source context and failure states.
  • AI components must remain separate from business logic.

What I can build

  • RAG and local LLM integrations
  • Structured extraction pipelines
  • AI-assisted documentation and human-review workflows

Typical deliverables

  • AI prototype or proof of concept
  • RAG system
  • Structured extraction pipeline
  • Traceable AI backend

Relevant technologiesLocal LLMs · RAG · Embeddings · Structured outputs · Speech-to-text · FHIR

How I can help

Architecture & Integration Consulting

For a new system or a difficult existing one, I help make technical boundaries, data contracts and evolution paths explicit before they become expensive to change.

Typical challenges

  • The architecture is hard to extend or reason about.
  • FHIR was added after the core system was built.
  • Roles, authentication and patient identity lack a stable model.

What I can build

  • Architecture reviews and system design
  • API, security and integration strategy
  • Migration planning and technical decision records

Typical deliverables

  • Architecture review
  • System design and diagrams
  • Security engineering recommendations
  • Migration plan and technical roadmap

Relevant technologiesAPI architecture · OAuth · OpenID Connect · Docker · FHIR · PostgreSQL

Typical engagements

Concrete ways to start.

  • Build a HealthTech MVP
  • Add FHIR support to an existing application
  • Build an HL7 v2 → FHIR adapter
  • Design a healthcare backend with explicit access boundaries
  • Prototype a clinical AI workflow
  • Review an existing HealthTech architecture
  • Integrate HAPI FHIR
  • Build a clinical data pipeline

Who this is for

For teams building in a healthcare context.

A good fit when software, clinical information and technical decisions meet in the same project.

  • HealthTech startups
  • Healthcare software teams
  • Care providers
  • Clinics
  • Digital health projects
  • Research-oriented healthcare teams

Start a conversation

Have a healthcare software problem?

Let’s talk about the system behind it.

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