Compensation:

National: $114,000-$160,000

NYC/SF: $120,000-$170,000

Tempus AI is a cutting-edge clinical laboratory coupled with powerful automation capabilities. We continually strive to deliver quality results to our patients as quickly as possible. As a Lead QA Engineer, you will own the quality engineering strategy for a portfolio of in-house developed clinical software, including a HIPAA-compliant clinical order platform and its supporting data-query and ETL tooling, and you will be the senior-most technical voice on how we prove that software works. You will set the test architecture and automation standards that our Senior and mid-level QA engineers build against, own nightly regression and CI/CD test orchestration end to end, and lead release readiness and go/no-go decisions with evidence rather than opinion. Knowledge of genetic testing, molecular biology, or other scientific disciplines is a strong plus but is not required. This is a fantastic opportunity to shape how quality is engineered across a growing clinical software organization.

Key Responsibilities
• Own the end-to-end quality engineering strategy across the application portfolio: test architecture, tooling selection, coverage targets.
• Set and enforce the automation framework architecture across multiple suites and repositories, reusable page objects and fixtures, shared utilities, dependency and version management, stable selectors, and act as the final reviewer on test-framework pull requests.
• Own CI/CD test orchestration end to end (GitHub Actions or equivalent): deployment-triggered and nightly regression runs, health checks, artifact and version gating, reporting, and automated notification.
• Lead release readiness and go/no-go: consolidate risk assessment, validation evidence, and quality metrics into a clear recommendation for engineering and product leadership.
• Drive shift-left across the Agile Scrum teams you support, represent quality and testability in design reviews, requirements, and definition of ready/done, and build quality gates into the delivery pipeline rather than at the
end of the sprint.
• Own the compliance posture of our test practice for regulated components: HIPAA and SOX coverage, PHI handling, access controls, audit trails, and requirement-to-test-to-result traceability. Serve as the QA point of
contact for audit and validation activities.
• Define, publish, and act on quality metrics, automation coverage, flake rate, escape rate, MTTR, and regression runtime, and hold the organization to an improvement trend.
• Mentor and grow the QA/SDET team, including Senior engineers: code review, pairing, framework onboarding, technical roadmap, and career development. Partner with hiring managers on interviewing, leveling, and onboarding.
• Serve as the final escalation for complex or systemic failures that span product, environment, test data, and harness, and drive root cause to resolution across team boundaries.
• Set the standard for non-functional testing (performance, load, resilience) and for responsible AI-assisted QA workflows, test authoring, failure triage, and coverage analysis, while keeping the team accountable for the correctness of every test that ships.
• Partner with software engineering, DevOps, and product leadership, and represent quality in architecture, platform, and release-process decisions.
• Stay hands-on: personally design, build, and maintain automation for the highest-risk areas of the portfolio, and validate scheduled night-time and off-hours deployments in lower and production environments.

Qualifications
• 10+ years of experience in software QA or test engineering, with 7+ years of hands-on test automation, including 3+ years as the lead, staff, or principal-level technical owner of a test practice.
• Demonstrated track record of owning test architecture and automation standards across multiple applications or teams, not just within a single suite.
• Expert-level programming ability in Java and/or Python, with strong design instincts (Page Object Model, dependency management, avoiding brittle waits and copy-paste tests) and a habit of treating test code as production code.
• Deep hands-on experience with modern browser automation (Playwright and/or Selenium WebDriver) and test runners such as JUnit 5 or TestNG, built with Maven or Gradle.
• Deep hands-on experience with API test automation and tooling (e.g., REST Assured, Postman), including status/schema/contract validation and authentication flows.
• Experience owning automation in CI/CD (GitHub Actions, Jenkins, GitLab CI, Bamboo, or similar): pipeline design, scheduled and triggered runs, artifacts, and test reporting such as Allure.
• Advanced SQL and relational database skills (e.g., MySQL), plus a defensible approach to test data management for regulated data.
• Experience setting performance and load testing strategy, with hands-on use of tools such as JMeter, k6, or Gatling.
• Experience with cloud-native delivery, especially AWS (ECS/Fargate, Lambda, S3) or Azure, and with containers (Docker) for reproducible, parallelized test execution.
• Practical use of observability tooling (e.g., Datadog, CloudWatch) and application logs to investigate defects and validate non-functional behavior.
• Working knowledge of healthcare standards and compliance (HIPAA, SOX, HL7, FHIR, and similar), and of testing in a validated or regulated environment.
• Proven mentorship of Senior and mid-level engineers through pairing, code review, and framework onboarding.
• Excellent verbal and written communication skills, including the ability to explain quality risk and trade-offs to executive and non-QA stakeholders.
• Ability to set technical direction and drive multi-quarter initiatives independently, making pragmatic trade-off between coverage, speed, and effort.
• Bachelor's or advanced degree in Computer Science or a related discipline, or equivalent professional experience.

Preferred
• ISTQB/ASTQB certification, Advanced Level or above.
• Experience in a CLIA/CAP laboratory, FDA-regulated, or SOX-controlled software environment, including audit support.
• Experience building or operating AI/LLM-assisted QA workflows, automated failure summarization, test generation, or agent-based regression triage.
• Knowledge of genetic testing, molecular biology, or other scientific-related disciplines.

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