Senior Software Engineer at ComPsych Corporation

Job description

ComPsych Ⓡ is the worldwide leader in organizational mental health, well-being, and absence management, dedicated to igniting human potential in workplaces across the globe. For over 40 years, we have combined the best in technology with unmatched human expertise to help individuals and their organizations thrive. Our GuidanceResources Ⓡ and AbsenceResources Ⓡ solutions deliver end-to-end mental health, well-being, work-life, health navigation, and absence support to more than 75,000 customers worldwide, touching more than 160 million lives across 200 countries. Visit compsych.com to find out why 40% of the Fortune 500 choose ComPsych for their mental health and absence management needs. We're modernizing how ComPsych builds technology — new customer-facing web and mobile experiences, a unified design system, and AI-powered capabilities across our products. That means raising the engineering bar for how we design, build, and operate software, with Engineering, Product, and Design working together end to end. We're looking for a Senior Software Engineer who has hands-on experience with modern, AI-led development practices and wants to help shape how our engineering organization builds software going forward. This is a high-leverage role: you'll spend more time on system design, task decomposition, and technical direction than on writing code line-by-line. You'll use AI tools to generate code, automated tests, and first-pass reviews, then apply your own judgment to validate and refine that output before it ships. AI changes what your time goes toward. You're still accountable for the full lifecycle — planning, design, code, tests, review, production — but your hands-on role in each shifts: • Plan and design as your core contribution. You own problem framing, sequencing, and tradeoffs with Product and Design, and the system design that follows — the data model, the API contracts, the failure modes. • Direct implementation rather than writing it line by line. Decompose the work, write the specs, and let AI agents build — dropping into the code yourself when debugging or complexity demands it. • Own testing as a design decision. You decide what needs coverage and at what level, direct AI to build it, and validate that the tests prove what they claim — not just that they pass. • Build security, reliability, and observability in from the start. They're design inputs, not production afterthoughts — the systems you ship can be operated safely and understood when they fail. • Review everything with the same rigor, regardless of author, and keep production judgment human. You're accountable for what ships whether you or an agent wrote it. Deployment calls, on-call response, and what an incident teaches you stay yours. • Raise the bar for how the team works with AI, coaching engineers to specify, delegate, and validate rather than hand-code everything themselves. • Deep server-side experience in a modern language such as Java, Python, C#, Kotlin, or Go. You've owned services end to end, not just features inside someone else's, and can pick up ours quickly. • Must have 5+ years of full stack development experience. • APIs and data models other people depend on: REST contracts, versioning, OAuth2/OIDC, schema design, and SQL that holds up under real load. • Async and event-driven systems in production — Kafka or comparable, idempotency, and a clear view of what at-least-once costs you downstream. • You've built and operated production systems at real scale on AWS or Azure — containers, Kubernetes or serverless, IaC, and CI/CD pipelines you've built, operated, or materially improved. You've carried the on-call load for them, so you know what “good” looks like independent of who or what wrote the code. • A testing strategy you can defend — what belongs at unit, integration, and contract level, and how you know a release is verifiable before it ships. • Reliability and security you've been accountable for: SLOs you’ve been paged against, incidents you led, OWASP and threat modeling applied — and PHI/HIPAA or comparable regulated-data experience. • Agentic AI is your primary development surface, and you catch what it gets subtly wrong. Not occasional autocomplete, not a hunch — you've shipped and operated real production systems working 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. • Full benefits package, including Paid Time Off (PTO), medical, dental, vision, 401(k) with match, robust EAP, wellness program, and much more • The salary range for this position is $150,000 - $200,000 (USD). The base salary range represents the anticipated low end and high end of the range for this position. The actual compensation will be influenced by a wide range of factors including, but not limited to previous experience, education, pay market/geography, and scheduled hours. EEO ComPsych is an equal opportunity employer. All applicants will be considered for employment regardless of race, color, age, genetics, religion, gender, sexual orientation, gender identity, national origin, disability or protected veteran status and any other characteristic protected by federal, state or local laws. ComPsych Corporation maintains a drug free workplace. ComPsych Corporation and its affiliates is committed to the responsible and transparent handling of your personal data. Information collected during the recruitment process will be used to assess your application and, where applicable, to prepare and administer an offer of employment. Your personal data will be processed in accordance with the privacy laws applicable in your country or jurisdiction of residence, which may include the California Consumer Privacy Act (CCPA), the EU General Data Protection Regulation (GDPR), Canada's Personal Information Protection and Electronic Documents Act (PIPEDA) and applicable provincial privacy legislation, and other applicable national or local privacy laws. For full details on what personal data we collect, how we use it, your rights as an Applicant, and how to contact us with privacy-related questions, please review the relevant Applicant Data Privacy Notices: US Applicant Data Privacy Notice & Canada Data Privacy Notice .

Requirements

Must-haves

AI changes what your time goes toward. You're still accountable for the full lifecycle — planning, design, code, tests, review, production — but your hands-on role in each shifts:
Plan and design as your core contribution. You own problem framing, sequencing, and tradeoffs with Product and Design, and the system design that follows — the data model, the API contracts, the failure modes.
Direct implementation rather than writing it line by line. Decompose the work, write the specs, and let AI agents build — dropping into the code yourself when debugging or complexity demands it.
Own testing as a design decision. You decide what needs coverage and at what level, direct AI to build it, and validate that the tests prove what they claim — not just that they pass.
Build security, reliability, and observability in from the start. They're design inputs, not production afterthoughts — the systems you ship can be operated safely and understood when they fail.
Raise the bar for how the team works with AI, coaching engineers to specify, delegate, and validate rather than hand-code everything themselves.
Deep server-side experience in a modern language such as Java, Python, C#, Kotlin, or Go. You've owned services end to end, not just features inside someone else's, and can pick up ours quickly.
Must have 5+ years of full stack development experience.
APIs and data models other people depend on: REST contracts, versioning, OAuth2/OIDC, schema design, and SQL that holds up under real load.
Async and event-driven systems in production — Kafka or comparable, idempotency, and a clear view of what at-least-once costs you downstream.
A testing strategy you can defend — what belongs at unit, integration, and contract level, and how you know a release is verifiable before it ships.
Reliability and security you've been accountable for: SLOs you’ve been paged against, incidents you led, OWASP and threat modeling applied — and PHI/HIPAA or comparable regulated-data experience.

Nice-to-haves

Bonus: LLM application engineering (RAG, retrieval quality, evals, LLM observability), or modern TypeScript frontend work against a design system.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

design systemaiapijavapythonkotlingorestsqlawsazurekubernetesci/cdllmtypescript

Platform: icims
Effort: medium

Benefits

Benefits detected in the listing.

Dental

Vision

401(K)

Pto

Paid Time Off

Wellness