6+ years in backend engineering, with at least 2 years 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 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.

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.

6+ years in backend engineering, with at least 2 years 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 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.

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.

Software Development Engineer III - Backend, Java

Skills