About the Role
AssureCare's platform is only as valuable as its connections to the systems our customers already run. As an Integration Engineer, you own those connections — the APIs, event-driven integration hubs, and message queues that move clinical, claims, and member data reliably between customer systems and our platform. In healthcare, the integration is where the value is realized, and where most projects stall; getting it right is the core of this role.
This is a senior, hands-on role for an integration engineer who is equally comfortable with traditional enterprise integration and modern AI tooling. Day-to-day you build and support customer and partner API integrations; alongside that, you apply your AI skills to make those workflows smarter. You will ship production features, help set standards for how we build safely, and turn both integrations and AI capabilities into reliable outcomes that improve care and shorten delivery timelines.
What You'll Do
- Own the integration layer. Build and maintain the REST/Web APIs, webhooks, event streams, and integration hubs that connect customer, partner, clinical, claims, and member systems to the AssureCare platform — using Azure Integration Services and message-based architectures.
- Deliver customer integrations. Build and support the day-to-day customer and partner API integrations — data exchange, third-party services, and interoperability — from scoping and onboarding through go-live and ongoing support.
- Engineer for resilience. Treat every integration and AI call as an unreliable dependency — timeouts, retries with backoff, circuit breakers, idempotency, dead-letter handling, and graceful fallback so member-facing workflows never fail loudly.
- Build compliance in, not on. Deliver integrations that meet HIPAA and PHI requirements from day one: identity propagation, least-privilege access, PHI minimization and redaction, full audit trails, and clear data-flow documentation — and hold AI-touched data to the same bar.
- Apply AI to the workflow. Use your AI skills to design, build, and operate AI-powered features that run reliably inside the integrations you own, across AssureCare's platform and our customers' systems.
- Integrate foundation models. Connect LLM provider APIs and SDKs (Azure OpenAI, Anthropic Claude, OpenAI, and comparable) using structured outputs, retrieval-augmented generation (RAG) over clinical and policy knowledge, and tool/function calling.
- Design human-in-the-loop workflows. Build automation for clinical documentation, prior authorization, and intelligent document processing that keeps a clinician or reviewer in control of every consequential decision.
- Build the evaluation model. Design and build the evaluation model for our AI systems — test sets, scoring criteria, and automated regression checks — and pair it with prompt/version management and observability across quality, latency, and cost, so AI behavior is measured and regressions are caught before they reach members.
- Govern the model layer. Route across multiple AI providers through a gateway, manage spend and rate limits, and judge when to use a platform's native AI capability versus building a custom integration.
- Roll out safely. Use feature flags and staged, per-customer rollouts to release integrations and AI capabilities incrementally and catch regressions before they affect everyone.
- Raise the engineering bar. Provide peer code review, mentorship, and technical decision-making; help establish best practices and standards for integration and AI-assisted engineering across a global, Agile team.
- Drive AI-assisted delivery. Champion AI coding and troubleshooting tools (e.g., GitHub Copilot, Claude) to accelerate development, improve code quality, and reduce delivery timelines.
- Translate across the room. Communicate technical options and trade-offs to clinical, product, security, and customer stakeholders, and turn business requirements into shippable technical solutions.
Languages & Frameworks
- C#, .NET (Framework 4.5+ / .NET Core), Python or TypeScript, ASP.NET, REST Web API
- Integration & Messaging
- Azure Integration Services (API Management, Logic Apps, Service Bus, Event Grid), webhooks, RabbitMQ / Kafka / MSMQ
- AI & LLM
- Azure OpenAI, Anthropic Claude, OpenAI; RAG, structured outputs, function/tool calling, MCP; evals & prompt management
- Cloud & Data
- Microsoft Azure, SQL Server, Entity Framework, serverless and N-tier architectures
- Healthcare & Interoperability
- FHIR, HL7, healthcare interoperability, intelligent document processing, clinical documentation, prior authorization
- Security & Compliance
- HIPAA / PHI, OAuth 2.0 / OIDC / SAML, audit logging, data residency, least-privilege access
- Observability & Delivery
- LLM observability (e.g., Langfuse / Helicone), APM, feature flags, CI/CD, Agile / Scrum
What We're Looking For
- Experience. 6+ years designing, building, and shipping production software and integrations.
- Integration fundamentals. Strong command of REST/Web API design and consumption, webhooks, idempotency, and event-driven or message-queue patterns (Service Bus, RabbitMQ, Kafka, or MSMQ).
- Customer integration experience. Track record delivering API integrations for customers or partners end-to-end — scoping, building, testing, and supporting reliable data exchange between systems.
- Core engineering. Professional experience with C# and .NET (4.5+ and .NET Core), SQL Server and stored procedures, and object-oriented design; fluency in Python or TypeScript for integration work.
- Cloud & architecture. Hands-on Azure experience and a track record designing scalable, N-tier and serverless systems.
- AI skills. Practical, hands-on experience applying AI in real applications — calling LLM provider APIs and SDKs (Azure OpenAI, Anthropic, OpenAI, or similar), building RAG pipelines, and working with structured outputs and function/tool calling.
- Evaluation model. Proven ability to build an evaluation model for AI systems — defining test sets, scoring criteria, and automated regression checks that measure output quality and gate what reaches production.
- Judgment on AI output. Ability to evaluate AI-generated code and model output for correctness, security, scalability, and maintainability.
- Security mindset. Experience delivering solutions under healthcare security, privacy, and compliance requirements (HIPAA, PHI), including authentication (OAuth 2.0 / OIDC / SAML) and audit.
- Communication. Excellent written and verbal communication; able to explain technical trade-offs to non-technical and clinical stakeholders.
- Ways of working. Comfortable in a fast-paced Agile/Scrum environment, working both independently and as part of a global team, and eager to learn new technologies quickly.
- Education. Bachelor's degree in computer science, engineering, or a related field preferred; equivalent work experience will be considered.
Preferred Qualifications
- Healthcare AI workflows. Experience building or integrating AI for clinical documentation, prior authorization, FHIR-based solutions, healthcare interoperability, or intelligent document processing.
- Integration hubs & iPaaS. Hands-on experience with Azure Integration Services, MuleSoft, Workato, or comparable integration platforms.
- Model Context Protocol (MCP). Experience exposing tools and data to AI systems via MCP or similar emerging standards.
- Agentic systems. Experience designing multi-step agent workflows with robust human-in-the-loop controls.
- Observability & FinOps. Experience with LLM observability tooling and managing AI cost and latency at scale.
- Automation mindset. A track record of spotting where AI can automate manual processes and improve operational efficiency and product capabilities.
