Requirements :

- 6+ years in backend engineering, with at least 2 in a lead or tech-lead capacity.

- Strong proficiency in Java, Spring Boot, Hibernate/JPA, and microservices.

- Demonstrated experience in HLD and LLD and in designing, building, and deploying microservices-based systems in production.

- Hands-on agentic SDLC experience within the last 12 months : you have shipped production software where AI agents were a primary part of the workflow. Concretely, experience with tools such as Claude Code, Cursor, Codex, Devin, Copilot Workspace/agent mode, Aider, or equivalent, applied to at least three of design, implementation, code review, test generation, and production debugging/monitoring.

- Practical judgment about where agents fail in context management on large codebases, hallucinated APIs, silently wrong tests, review fatigue, and concrete mitigations you've put in place.

- Solid grounding in Git, CI/CD, and automated testing, including how these change when a large share of diffs are agent-authored.

- Strong SDLC fundamentals and a track record of working with multiple teams.

Nice to have :

- Built custom agents, subagents, or MCP servers against internal systems.

- Prompt/context engineering at the repo scale (e. g., CLAUDE, MD-style instruction files, retrieval over internal docs, codebase indexing).

- Experience with LLM evaluation, regression harnesses, or accuracy pipelines.

- Observability tooling (New Relic, Datadog, Prometheus/Grafana) and agent-assisted incident triage.

- Healthcare, FHIR/HL7 or medical coding domain exposure.

- Python for tooling and data work; PostgreSQL, Elasticsearch, or Neo4j; GCP or AWS.