Established in 1833, McKesson is a US Fortune 10 global leader in healthcare supply chain management solutions, retail pharmacy, healthcare technology, community oncology, and specialty care.
Based in Bangalore, India, our Compile data provides a comprehensive, full linked system of record for the US healthcare market, with intelligence on 2M+ healthcare professionals and over 800K facilities. It includes high‑capture medical and pharmacy claims, closed‑capture Medicare claims (100%), and best‑in‑class provider affiliations.
Senior Software Engineer (P2) – Full Stack (Java, Spring Boot, React)
Location: Bangalore, India (Hybrid)
Experience: 4–7 years
Domain: Healthcare Technology (Oncology / Clinical Platforms)
We are looking for a Senior Full Stack Software Engineer to design, build, and operate scalable, mission‑critical healthcare applications. This is a backend‑first full‑stack role (70% backend / 30% frontend) where you will primarily work on Java + Spring Boot microservices while contributing to React‑based UI layers to deliver end‑to‑end features.
You will operate in an AI‑first engineering environment, using tools such as GitHub Copilot, Windsurf, and Claude to accelerate development. Strong expectation that you validate, refine, and production‑ize outputs to meet security by design with enterprise‑grade standards.
Full Stack Development
- Design and build scalable microservices using Java, Spring Boot, and REST APIs
- Define clear API contracts (OpenAPI/Swagger) with consistent error handling and versioning
- Implement event‑driven architectures using Kafka or equivalent messaging systems
- Build high‑performance data access layers using JPA/Hibernate and Oracle/Postgres
- Develop and enhance UI components using React.js and TypeScript
- Build integration layers and admin UIs to support backend workflows
- Ensure end‑to‑end flow validation (UI → API → DB → events)
- Ensure production‑grade reliability: transaction safety, idempotency, and error recovery
AI‑First Engineering Mindset (Critical)
- Actively use AI tools (e.g., GitHub Copilot, Windsurf, Claude or any other McKesson‑approved tools) to:
- Accelerate coding, refactoring, and test generation
- Improve developer productivity without compromising maintainability
- Critically evaluate AI‑generated code for:
- Correctness and edge cases
- Security and data handling risks
- Performance and scalability
- Apply AI responsibly in:
- Code generation, debugging, and clear documentation
- Unit test case creation and coverage improvement
- Design systems that are AI‑friendly (clear APIs, structured data, consistent contracts)
- Observable and diagnosable using logs, metrics, and traces
- Security by design
Engineering Quality & Delivery
- Write clean, maintainable, well‑tested code (unit + integration tests)
- Participate in code reviews, design discussions, and architecture decisions
- Work in Agile teams with strong accountability and ownership of delivery
- Diagnose and resolve production issues using observability tools, such as Dynatrace
Platform & System Thinking
- Build services that are reusable, well‑documented, and easy for other products to integrate
- Follow best practices in API design, microservices architecture, CI/CD and DevOps pipelines
Minimum Requirement
- Degree or equivalent relevant experience
Must‑Have Skills
- 4–7 years of software development experience in product/enterprise environments
- Strong hands‑on experience with Java (17+) and Spring Boot
- REST API design and microservices architecture
- Experience with React.js + TypeScript (at least 1‑2 years)
- SQL and relational databases (Oracle/Postgres)
- ORM tools (Hibernate/JPA)
- Event‑driven systems (Kafka or similar)
- Caching (Redis or similar)
- CI/CD pipelines and Git‑based workflows
- Automated testing practices
- Strong debugging and production issue analysis skills
AI‑First Expectations (Non‑Negotiable)
- Practical use of AI coding assistants in development workflow
- Ability to review, validate, and production‑harden AI‑generated code
- Understanding that:
- AI accelerates development
- Engineers are still accountable for design, correctness, and quality
Foundational
- Clear written and verbal communication – ability to document services and explain technical decisions
Good‑to‑Have Skills
- Healthcare domain experience
- Familiarity with FHIR / HL7 / C‑CDA standards
- HIPAA compliance and PHI/PII handling
- Experience with Databricks / data pipelines
- Elasticsearch / Redis
- Docker / Kubernetes
What Success Looks Like
- Deliver production‑ready features end‑to‑end, not just code
- Build systems that are scalable, observable, and reusable
- Improve team productivity using AI without degrading quality
- Contribute to raising engineering standards across the team
Why This Role Stands Out
- Work on real‑world healthcare systems impacting patient outcomes
- Exposure to modern architecture and AI‑driven engineering practices
- Opportunity to build platform‑grade services used across multiple teams