Sr. Java Developer

Responsibilities

• Design, develop, test, and deploy Java microservices on GCP; implement resilient, observable services in a microservice architecture.
• Build responsive front‑end applications using Angular (component‑driven patterns, RxJS).
• Implement messaging/streaming integrations using Kafka and GCP Pub/Sub; design for at‑least‑once/exactly‑once semantics and back‑pressure.
• Work with GCP Kubernetes (GKE) for container orchestration; automate CI/CD and promote builds across environments.
• Model and optimize data access on Cloud Spanner; contribute to schema design, transaction strategies, and performance tuning.
• Own E2E quality: unit, integration, contract, and performance testing; drive high code coverage and automated quality gates.
• Collaborate across architecture, data modeling, security, and product teams; demo features, capture feedback, and iterate quickly.
• Document LLD/sequence diagrams, and contribute to coding standards, architecture guidelines, and re‑usable libraries.
• Support production (SRE/Dev Ops mindset): monitoring, incident response, and RCA.

• Engineering Degree – BE/ME/BTech/MTech/BSc/MSc.
• Technical certification in multiple technologies is desirable.

• Strong 10+ years of professional software engineering experience;
  Java 8+ in production.
• 4+ years recent, hands‑on Spring ecosystem (Spring 4/5,
  Spring Boot 2+, Spring Data, Spring Cloud, Spring Integration, Spring REST).
• Event‑driven / asynchronous architecture; 4+ years integrating with brokers (Kafka / Pub/Sub) and applying appropriate design patterns.
• GCP hands‑on
  : GCS Buckets,
  Kubernetes (GKE),
  Pub/Sub
  , Kafka
  ; infrastructure and services usage in production.
• Cloud Spanner experience (or strong No
  
  SQL exposure with Cassandra/Couchbase and proven ability to ramp).
• Strong testing discipline: JUnit5, Spring test (unit/integration), isolated layer testing, Hamcrest/Assert
  
  J; mocking & debugging.
• Modern tooling:
  Git (enterprise workflows),
  Gradle/Maven
  , Intelli
  
  J (preferred) or equivalent; CI/CD (Jenkins/Git Hub Actions/Sonar).
• Clear communication, stakeholder engagement, and cross‑functional collaboration.
• Gen AI / Agentic AI exposure to build workflows and agents using ADK, A2A and MCP.

• Windsurf AI (developer productivity/AI‑assisted workflows).
• GCP Dataflow (batch/stream processing).
• US healthcare context—clinical data, medications, orders, labs.
• Angular/React (recent production experience).