Staff Software Development Engineer in Test

AI isn't a productivity add-on here — it's how we build. Our team uses agentic development as standard equipment, moving from problem to production-ready code faster than traditional development allows, while keeping the work reviewable and maintainable. We're looking for a Staff SDET who already works this way. Quality here is an engineering discipline, not a phase, and there is no manual QA layer beneath our SDETs: you own the strategy, automation, and signal quality for your team, with exploratory testing as deliberate work alongside maintainable automation. Agents help turn requirements into scenarios, generate automation, and diagnose failures; you own the judgment on whether the evidence is trustworthy. As a healthcare company, PHI never enters non-production environments. Platform owns environments and pipelines, and you own what runs on them: test configuration, data, and signal quality.

This role is for an SDET who has built testing frameworks and standards that multiple engineers and teams have adopted. You'll set testing direction across teams, define how ComPsych tests software, and make the right way the easy way.

What You'll Do

AI changes what your time goes toward. You're still accountable for the quality of what ships — strategy, automation, feedback, and data — but your hands-on role in each shifts:

• Build automation architecture and standards other teams build on. Design frameworks, fixtures, and shared patterns for reliable parallel execution, accounting for concurrency, asynchronous behavior, and eventual consistency. Set the testing practices engineers follow, and drive adoption through usefulness and influence rather than authority.
• Own quality strategy across teams. Define verification strategy for systems based on risk, decide what evidence each layer needs, direct exploratory effort at unfamiliar failure modes, and state what is deliberately not tested and why. Raise the quality bar beyond your own team.
• Make test feedback actionable. Own execution speed, gating, failure classification, and flake discipline so developers can self-resolve failures rather than routing every red build through you.
• Own synthetic data and PHI guardrails. Define the synthetic-data strategy, isolation patterns, and CI protections that keep PHI out of non-production while giving engineers deterministic test state.
• Set testability and non-functional quality where risk warrants. Define environment, observability, and data needs with Platform rather than building a parallel one, and set the depth of performance, resilience, accessibility, and security verification.
• Direct AI-first quality practice, and keep judgment human. Author agent conventions as versioned, reviewable artifacts, set boundaries for what agents may do without review, and treat a generated test that passed once as a draft, not a test.

What We're Looking For

Everyone in this role brings the foundations below, plus the role-specific depth that follows.

Foundations

• You're strong in a modern programming language and can reason about concurrency, asynchronous workflows, and failure propagation across services.
• You can trace a failing test across services using logs, traces, and deployment context, and tell whether the root cause is product, automation, data, or environment.
• You communicate residual risk clearly to Engineering and Product, including when shipping with a known gap is the right call, without becoming the release bottleneck.
• You have real depth in at least one non-functional area — performance, resilience, security, or accessibility — and know when to bring in specialists.
• You already work AI-first. You've set conventions other engineers actually followed and can explain where you draw the line on what an agent may change without human review.

Framework and standards builder (required)

• You've built a testing framework or shared automation platform that multiple engineers or teams adopted, and can show how it changed the way they work.
• You've defined testing standards and best practices, such as test-layer guidance, flake policy, and gating criteria, and driven adoption without relying on authority.
• You've designed or evolved a quality system across teams, not just automation for features. You translate product and architectural risk into a verification strategy and explain what you chose not to test.
• You've set technical direction beyond your own team, influencing roadmap, tooling, and tradeoffs across Engineering, and mentoring other engineers into the standards you set.

Bonus: experience verifying LLM-backed or other non-deterministic products; synthetic-data strategy and deterministic isolation for sensitive data; failure injection or recovery testing in production-like environments; or working in healthcare, another regulated domain, or systems that handle sensitive customer data.

Compensation And Benefits

• 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 $160,000 - $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 .

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