AI Backend Engineer

The InRhythm Opportunity InRhythm is establishing a modern software engineering practice built around an AI-driven Development Lifecycle (AI-DLC) methodology — spec-driven, agentic, and powered by Claude. As an AI Backend Engineer, you will work fluidly across Node.js and Java, using Claude as your primary coding partner to implement, test, and refine backend features at a pace that manual development cannot match. You are not a passive consumer of AI output. You are an expert reviewer, a disciplined operator of agentic workflows, and a craftsperson who holds the quality bar on everything that reaches the main branch. Your Impact You are where spec meets code. Your ability to rapidly iterate with Claude, catch subtle AI-generated errors, and maintain engineering discipline under delivery pressure directly determines the pod’s throughput and the quality of the enterprise platform you are accelerating. You represent the standard of what an AI-augmented engineer looks like, and your workflow discipline will be visible to client engineering teams.

What You Will Do

• Implement Specs with Claude: Use agentic workflows (Claude Code or equivalent) to implement backend Node.js and Java services from structured specifications.
• Review AI-Generated Code: Critically assess Claude’s output for correctness, security, performance, and alignment with existing codebase patterns. Never merge without rigorous human review.
• Write and Validate Tests: Review, extend, and where necessary write Jest/Mocha unit tests for Node.js and JUnit/Mockito tests for Java, including test output generated by or alongside Claude.
• Maintain Prompt Context: Contribute to and consume codebase context packs, coding convention documents, and prompt libraries maintained by the AI Solution Owner.
• Iterate on Specs: Flag ambiguities or gaps in specifications before agentic generation begins, saving rework cycles and improving spec quality over time.
• Own Your Delivery: Take full responsibility for features from spec handoff through production deployment, including CI/CD pipeline validation, SAST finding remediation, and post-deploy verification.

What You Will Bring Must Have Experience:

• Node.js Proficiency: 5+ years of production Node.js development with solid understanding of Express/Fastify/NestJS, async patterns, middleware design, and RESTful/GraphQL API design.
• AI-Augmented Development Experience: Demonstrable experience using AI coding agents (Claude Code, GitHub Copilot, Cursor, or equivalent) as a primary delivery tool, not just for autocomplete.
• Test-Driven Discipline: Ability to evaluate, extend, and own automated test suites including unit, integration, and E2E, including AI-generated test output.
• AWS Fundamentals: Working knowledge of AWS services relevant to application deployment including CDK, Lambda, DynamoDB, EKS, RDS, S3, API Gateway, and CloudWatch.
• Code Review Rigor: Ability to identify subtle bugs, security vulnerabilities, and anti-patterns in AI-generated Node.js and Java code.

Nice to Have Experience:

• React Proficiency: Experience building React applications with TypeScript, component architecture, and state management.
• Java Proficiency: Hands-on experience in production Java development with solid understanding of Spring Boot, Spring MVC, Spring Data JPA, Spring Security, and RESTful API design.
• UI Testing Frameworks: Familiarity with Cypress, Playwright, React Testing Library, or equivalent frontend testing and automation tools.
• Experience with prompt engineering for code generation tasks including context structuring, few-shot examples, and constraint specification.
• Familiarity with SAST tooling (SonarQube, Checkmarx, or equivalent) and secure coding practices for Node.js and Java applications.
• Exposure to BDD/Gherkin specification formats and their relationship to test automation.
• Experience in an enterprise financial services or similarly regulated codebase.