We’re looking for our next bold leader – a Senior Full-Stack Software Engineer, Clinical Intelligence – to join our quest to provide market-transforming solutions for businesses, care teams and consumers to interactively manage health and care.

At Medecision, you’ll have the chance to work with people that have incredible intellect, who are hard-wired for problem-solving. You’ll also know that you’re making a real difference, and not just in some abstract, corporate-mission-statement kind of way. We’re working with companies that touch millions of lives every day, maybe even saving a few along the way. Each person contributes uniquely to our mission and our ability to raise the level of experience we provide to all our customers and colleagues. The Senior Full-Stack Software Engineer on the Clinical Intelligence team plays a pivotal role in designing, building, and evolving the microservices backbone and React microfrontend UI layer of our care intelligence platform — spanning real-time rule execution, automated workflow processing, journey management, and the AI-native services that power clinical decision-making. They also serve as a key practitioner in Medecision's AI-native SDLC, leveraging Claude Code and AI agents to accelerate development, code review, and documentation at scale. 

 What We're Looking For 

To be successful at Medecision the Senior Full-Stack Software Engineer, Clinical Intelligence will demonstrate a true passion for building reliable, scalable, and secure full-stack systems in a regulated healthcare environment. They will share our passion for driving improvements in healthcare.

This role sits at the frontier of Medecision's agentic platform. The ideal candidate does not just use AI tools but actively builds with them: designing MCP-wrapped APIs that safely expose clinical platform capabilities to AI agents, contributing to agent orchestration pipelines, and enforcing rigorous guardrails for PHI handling, access controls, and audit logging across every agentic workflow. They internalize the idea that agents' toil belongs to agents and humans' critical decisions belong to humans, and they architect systems that maintain that boundary.  

Core Engineering Responsibilities

· Design, develop, and maintain Java/Spring Boot microservices and React microfrontend (MF) components on GCP — following     established service patterns, the Medecision MF architecture (runtime composition, atomic design), and a shared component library. 

· Build full-stack features end-to-end: RESTful APIs (service contracts, versioning, multi-tenant isolation) on the backend; TypeScript, Tailwind CSS on the frontend. 

· Implement event-driven workflows using Pub/Sub. 

· Own GitLab CI/CD pipelines end-to-end: build, lint, test, containerize (Docker), and deploy services and MF bundles to GCP; write JUnit 5/Mockito (backend) and Jest/React Testing Library (frontend) tests; author Storybook stories (story-first); use Datadog for backend and RUM observability. 

· Collaborate with on-shore and off-shore teams, architects, and tech leads to ensure on-time delivery and best engineering practices. 

· Engage proactively in the triage and resolution of escalated production issues — diagnosing failures, investigating root causes, and driving durable fixes with a sense of urgency, clear communication to stakeholders, and a commitment to preventing recurrence. 

· Follow and comply with all security policies and procedures established by the organization, including adherence to HIPAA and HITRUST regulations

· Applicants must be authorized to work for any employer in the US. This position does not offer sponsorship for employment visas.

Clinical Intelligence Domain Focus

· Design and develop backend services across core Clinical Intelligence modules — including real-time and automated rule execution, decision rules, program and population management, journey and campaign orchestration, and communications delivery. 

· Integrate with platform services (Population Data Service, Dictionary Service, Communication Service) and external partners; implement FHIR R4 integrations and healthcare interoperability workflows. 

· Contribute to the API and MCP layers — exposing platform APIs to AI agents with appropriate access controls and audit guardrails. 

AI-Native Delivery (Required)

· Use Claude Code as a primary productivity tool for code drafting, refactoring, test generation, and technical documentation — applying it with judgment, rigor, and accountability. 

· Contribute to building and exposing MCP-wrapped APIs that enable AI agents to safely interact with platform services. 

· Contribute to the team's shared AI knowledge base — validated prompts, skills, and workflows — and participate in the AI Champions community of practice. 

 Education and Experience 

Required

· Bachelor's  degree in Computer Science, Software Engineering, or equivalent practical experience. 

· 5+ years of backend engineering building production microservices in Java with Spring Boot (Spring Data JPA,     Security/OAuth2/JWT, OpenFeign, AOP, Actuator). 

· 3+ years of production TypeScript/React experience with microfrontend architecture (Module Federation, runtime composition, shell/remote MF pattern); proficiency with Vite, Tailwind CSS, TanStack React Query, Storybook, and Jest/React Testing Library. 

· Proven ability to design and implement RESTful APIs — including service contracts, versioning, error handling, pagination, and multi-tenant isolation patterns. 

· Understanding of multi-tenant SaaS architecture patterns — tenant context propagation, per-tenant feature flags, and data isolation. 

· Hands-on experience with Google Cloud Platform services: Cloud Run, Cloud SQL (PostgreSQL), Pub/Sub, Firestore, BigQuery, Secret Manager, Cloud Logging, Artifact Registry. 

· Experience with event-driven architecture and asynchronous processing patterns — designing and consuming Pub/Sub topics, handling message ordering, deduplication, and dead-letter queues. 

· Excellent communication skills — able to articulate technical decisions, participate in design reviews, and collaborate effectively with cross-functional teams. 

Strongly Preferred

· Knowledge of HIPAA and experience working in HIPAA-regulated product environments, including PHI handling, data classification, and audit requirements. 

· Hands-on experience with HAPI FHIR R4 and healthcare interoperability standards (HL7, FHIR resource mapping, validation workflows). 

· Exposure to the AI agent runtime stack: agent orchestration frameworks such as LangGraph (Python), FastMCP. 

· Experience  with infrastructure-as-code (Terraform) for provisioning and managing GCP environments. 

AI-Native Mindset (Required)

· Demonstrate a solid understanding of AI agentic concepts, capabilities, and limitations as they apply to software engineering workflows — including code generation, test scaffolding, and documentation. 

· Hands-on with Claude Code or equivalent as a daily productivity driver — not just experimentally; evaluates AI-generated code critically for hallucinations, logic errors, and security gaps. 

· Practical understanding of MCP (Model Context Protocol), or a strong willingness to learn it, for building tool wrappers that expose platform APIs to AI agents safely and with appropriate guardrails. 

· Applies AI with accountability: humans own decisions, agents own toil; zero tolerance for real PHI in AI-assisted workflows and commitment to mandatory HIPAA + AI training.