Java Developer w​/AI

Java (Spring Boot), Microservices, AWS, RestAPI, AI (Claude or Copilot), Dev Ops, Kafka

• Leads end-to-end delivery of full stack solutions using Java Spring Boot, GraphQL/REST, and AWS-managed services, from design through production support.
• Drives architecture and design reviews, defining service boundaries, API contracts, data models, and integration patterns.
• Develops secure, high-quality, production-grade code; conducts thorough code reviews; sets and enforces engineering standards.
• Builds and maintains highly available and scalable services with strong operational excellence: reliability, performance, cost awareness, and maintainability.
• Implements and governs authentication/authorization using OIDC/OAuth2, token validation, scopes/claims, and service-to-service security patterns.
• Establishes robust observability practices (structured logging, metrics, tracing), incident response readiness (runbooks).
• Evaluates vendor and internal solutions (including architectural fit, security posture, scalability, and operability) and guides adoption decisions

• Minimum 12+ years applied full stack engineering experience delivering and operating production systems; experience as a senior/lead capacity (technical leadership, design ownership).
• Java Spring Boot expertise: building APIs, dependency injection, validation, error handling, and performance tuning.
• GraphQL proficiency: schema design, resolvers, federation/composition patterns (where applicable), query performance (N+1 mitigation, caching), and API governance/versioning strategy.
• REST proficiency:
  OpenAPI-style contract design, pagination/filtering, idempotency, backward compatibility, and consumer-driven API evolution.
• OIDC/OAuth2: hands-on implementation with JWTs, refresh/access token flows, scopes/claims, secure session patterns, and least-privilege access control.
• AWS experience (hands-on): designing, deploying, and operating cloud-native applications; strong understanding of IAM, networking basics, and operational tooling (logs/metrics/alarms).
• Data layer expertise:
  • AWS Aurora PostgreSQL: advanced SQL, indexing, query optimization, migrations, and transactional design.
  • AWS Neptune: gremlin, graph modeling, query patterns, and performance considerations for graph workloads.
• Event-driven systems:
  • AWS Kafka (MSK): topics/partitions, consumer groups, schema evolution, ordering/at-least-once semantics, idempotency, retries/DLQs, and operational monitoring.
• CI/CD and quality:
  • Strong Git practices, automated testing (unit/integration/contract/e2e), code quality gates, and release confidence practices (feature flags, progressive rollout where applicable).
• AI-assisted engineering (MUST):
  • Demonstrated proficiency using Claude Code and/or Git Hub Copilot to accelerate development, debugging, refactoring, test generation, and documentation—while ensuring correctness, security, and maintainability (e.g., validating outputs, avoiding sensitive data leakage, and adhering to team standards