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About the Role

Software is entering a period where code generation isaccelerating,and verification is the new constraint. We are rebuilding our quality function from the ground up as an AI-first verification engineering team, and we are hiring founding SDETs to design and build it.This is not a test-case-writing role. You will build the verification infrastructure behavioral fences, property-based test suites, static analysis pipelines, and agentic QA workflows thatallowsAI-generated code to ship safely at high velocity. You will work directly with engineering leadership on one of the most consequential transformations in the company's history, with genuine authority to define how quality is engineered here.

What You'll Do

• Design and build behavioral fences(characterization harnesses that lock in existing behavior, and acceptance harnesses derived from specifications) that AI-generated code must pass beforemerge.

• Establish system-level behavioral baselines of our core product so agentic refactoring and extension can be verified against observable behavior.

• Build and own property-based testing suites (invariant-driven, generative input) targeting the failure modes characteristic of AI-authored code.

• Stand up andoperatethe non-behavioral verification stack: SAST/security scanning,secretsdetection, dependency/supply-chain analysis, and performance baselines in CI/CD.

• Develop agentic QAworkflowsAI agents that generate, execute, and triage tests with humans reviewing at the level of strategy and coverage, not individual cases.

• Define and report honest coverage boundaries: what is verified, what is sampled, and what is notcoveredso green dashboards mean what they claim.

• Implement observability for quality: logging, tracing, and metrics that surface verification signals,escapeddefects, and behavioral drift across the pipeline and in production.

• Participate in incident response and post-mortems for quality escapes, feeding every production defect back into the fences, suites, and pipeline as a permanent regression guard.

• Automate deployment of the verification infrastructure itselftestenvironments, harnesses, and pipeline tooling.

• Develop test strategies for AI-powered product features: prompt regression testing, behavioral boundary testing, output quality evaluation, and regression detection for non-deterministic outputs with observable quality signals defined alongside product and engineering.

• Partner with senior product engineers to route AI-generated defect fixes through the verification pipeline with human review at the right altitude.

What We're Looking For

• Strong software engineering fundamentals.You write production-quality code (Python, TypeScript/JavaScript, C#, Java, or Go) and think in systems, not scripts.

• Active use of AI coding assistants.Tools like Claude Code, Copilot, or Cursor are part of your daily workflow, andyou'regenuinely curious about how far they can be pushed you have opinions about where they fail and how to catch it.

• An instinct for testing invariants rather thanexamplesexperience with property-based tools (Hypothesis, fast-check,QuickCheck-family) is great evidence, but the mindset iswhat'srequired.

• CI/CD ownership.You have built or owned pipelines, not justconsumed themgates, quality signals, and tooling that other engineers rely on.

• Static analysis and security tooling familiarity(e.g.,Semgrep, SonarQube,CodeQL,Gitleaks) and an understanding of why input/output testing alone cannot catch security or performance rot.

• Performance and reliability awareness.Knowledge of performance tuning, capacity planning, and reliabilitypatternscorrect output at unacceptable latency or fragility is still a defect.

• Strong diagnostic and problem-solving skills for complex systems,and the ability to work collaboratively across development, QA, and operations teams.

• A builder's bias.You would rather build a harness that finds a whole class of bugs than manually find one bug.

What Sets You Apart

We know deep experience in these areas israrethe discipline is only a few years old.We'rebuilding it here, andwe'llinvest in developing it. Bring the fundamentals and the appetite; any of the following moves you to the top of the list:

• Agentic AI experience.Hands-on with Claude Code or comparable agents generating test scaffolding, accelerating authoring, analyzing coverage gaps, or building agentic workflows of your own.

• Experience testing or evaluating LLM-based systems.Evaluation frameworks (evals), model-graded testing, handling non-determinism, and qualitative evaluation (rubrics, rating systems, calibrated human review) where qualitycan'tbe reduced to assertions.

• Hands-on property-based or generative testingwith Hypothesis, fast-check, orQuickCheck-family tools in real projects.

• Supply-chainplanning, manufacturing, or ERP domain exposure.

• Experience characterizing legacy systems (snapshot/approval testing) ahead of large refactors.

• Performance and load-testing baseliningexperience.

• SRE or DevOps background on-call experience, chaos/resilience testing, or advocacy for test-driven development and resilience patterns.

Education & Experience

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years in software engineering, SDET, SRE, or DevOps roles.

Why This Role, Why Now

Most testing organizations are being disrupted by AI. This one is being built for it with executive mandate, from a clean sheet. You will be a founding member of the team that defines how an entire product organization ships AI-authored software safely. If you have been waiting for a role where verification engineering is treated as the product rather than the afterthought, this is it.

When applying, please include a short noteon the most interesting failure you have seen an AI coding agent produce.