Note: The job is a remote job and is open to candidates in USA. ComPsych is modernizing its technology through customer-facing web and mobile experiences, a unified design system, and AI-powered capabilities across its products. The Software Engineer will own well-scoped features or components end to end, using AI-led development practices for system design, implementation, testing, deployment, and production operations.
Responsibilities
- You own a well-scoped feature or component end to end — design, build, test, and how it behaves in production
- Plan and design within your scope. You translate requirements into a clear plan and specs an AI agent can execute against, working with Product and Design to clarify what's ambiguous rather than waiting for someone to resolve it
- Direct implementation rather than writing it line by line. Break the work into tasks, write the specs, and let AI agents build — and go hands-on in the code when debugging, unfamiliar territory, or a tricky edge case calls for it
- Own testing as a design decision. Decide what needs coverage, direct AI to build the tests, and validate that they actually prove what they claim
- Review everything with the same rigor, regardless of author. You catch the assumptions AI won't flag on its own, and you're accountable for what ships
- Own your feature in production. You deploy through your team's CI/CD pipeline, partner with DevOps rather than treat deployment as someone else's job, and you're the one who responds — and rolls back — when something breaks
- You write production services in a modern language such as Java, Python, C#, Kotlin, or Go, and can pick up ours quickly
- You build APIs and data models other code depends on — REST contracts, request and response validation, authentication, schema design, indexes, migrations, and SQL that holds up on real volume
- You ship and operate your own code in the cloud (AWS or Azure) — containers and CI/CD you can debug when the build or the deploy is what’s broken, plus on-call experience diagnosing a live issue from logs, metrics, and traces
- You write real tests, not coverage — unit and integration, with a view on which belongs where and what a test actually proves
- You write secure code by default — authorization checks, input validation, secrets handling, least privilege, and no PHI in logs
- You reason well about systems, data, and tradeoffs. You can sketch how what you're building fits together, spot where it's likely to fail, and think about who else is affected if it does
- Agentic AI is your primary development surface, and you catch what it gets subtly wrong. Not occasional autocomplete, not a hunch — you've shipped production code this way and can point to what you caught before it shipped
- Bonus: LLM application engineering (RAG, retrieval quality, evals, LLM observability), or modern TypeScript frontend work against a design system
Skills
- You write production services in a modern language such as Java, Python, C#, Kotlin, or Go, and can pick up ours quickly
- You build APIs and data models other code depends on — REST contracts, request and response validation, authentication, schema design, indexes, migrations, and SQL that holds up on real volume
- You must have 2 + years of full stack software development experience
- You ship and operate your own code in the cloud (AWS or Azure) — containers and CI/CD you can debug when the build or the deploy is what's broken, plus on-call experience diagnosing a live issue from logs, metrics, and traces
- You write real tests, not coverage — unit and integration, with a view on which belongs where and what a test actually proves
- You write secure code by default — authorization checks, input validation, secrets handling, least privilege, and no PHI in logs
- You reason well about systems, data, and tradeoffs. You can sketch how what you're building fits together, spot where it's likely to fail, and think about who else is affected if it does
- Agentic AI is your primary development surface, and you catch what it gets subtly wrong. Not occasional autocomplete, not a hunch — you've shipped production code this way and can point to what you caught before it shipped
- Bonus: LLM application engineering (RAG, retrieval quality, evals, LLM observability), or modern TypeScript frontend work against a design system
Benefits
- Full benefits package, including Paid Time Off (PTO), medical, dental, vision, 401(k) with match, robust EAP, wellness program, and much more
- Remote work arrangement
Company Overview
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