Come work at a place where innovation and teamwork come together to support the most exciting missions in the world! Qualys is looking for a Lead QA Engineer to own quality for products in the Cybersecurity and Compliance domain used by thousands of enterprise customers. You will act as a senior individual contributor and technical mentor for QA and automation engineers. You will define the test strategy across UI, backend, and data pipelines, and drive the move toward AI-assisted, self-healing automation. This is a hands-on technical role: you set quality direction, influence release decisions, and actively write and review framework code. Candidates who have built or meaningfully enhanced AI-based self-healing automation tools will stand out. Responsibilities QA Mentorship & Strategy • Mentor and guide QA and automation engineers through technical coaching, code reviews, and knowledge sharing. • Define and own the end-to-end test strategy for legacy components by improving automation coverage, while ensuring all new components are fully automated from the start. • Act as the quality voice in sprint planning, design reviews, and release readiness; make data-backed go/no-go recommendations. • Establish scalable QA processes: defect triage, severity/priority standards, regression tiers, test case management, and root-cause analysis for escaped defects. • Track and report quality metrics (defect leakage, automation coverage, flaky-test rate, mean time to detect, release cycle time) to engineering and product leadership. • Partner closely with Development, Product, Support, and Sustenance teams to shift quality left and reduce customer-reported issues. Test Automation (Hands-On) - Architect and evolve automation frameworks across React/TypeScript front ends, Java/Spring Boot microservices, REST APIs, and Kafka-based pipelines. - Own API and contract testing (REST Assured, Pact, Postman/Newman) covering OAuth2, JWT, token, and Basic auth flows, pagination, throttling, and vendor error handling. - Own CI/CD quality gates in Jenkins or GitHub Actions with fast PR-level feedback and tiered regression runs. AI-Driven & Self-Healing Automation - Lead the design and rollout of self-healing automation: automatic locator recovery, DOM-similarity scoring, element fingerprinting, and confidence-based fallback that keeps suites green through UI changes. - Apply LLMs across the QA lifecycle — generating test cases from requirements and API specs, converting manual tests to automated scripts, summarizing failures, and suggesting root causes from logs. - Build intelligent flaky-test detection, failure classification, and auto-quarantine to separate real regressions from environmental noise. - Set guardrails for AI use in QA — validating AI-generated tests, measuring healing accuracy, and preventing false passes. Qualifications Experience - 8-10+ years in QA / test engineering, with at least 2 years leading or mentoring a QA team. - Proven track record of building automation frameworks from scratch and owning release quality for a SaaS product. - Hands-on experience building, extending, or productionizing an AI-based or self-healing automation solution, with the ability to explain how you measured its impact. Skills Automation & Testing - Robot, Playwright and/or Selenium 4; TestNG or JUnit 5; Cypress, Jest, or Vitest - API automation: REST Assured, Postman/Newman, schema validation - Contract testing (Pact), service virtualization, and mocking (WireMock or similar) - Performance testing with JMeter, k6, or Gatling - Visual regression and accessibility testing Programming & Backend - Python, Java(17+) and JavaScript/TypeScript - SQL and data validation on Oracle or similar - Familiarity with microservices, Spring Boot, and Kafka (or other event streaming systems) AI in QA - Self-healing locator strategies and intelligent element matching - LLM integration: prompt design, structured outputs, and embedding model calls into test tooling - AI-assisted test generation, failure clustering, and log/trace summarization - Familiarity with RAG or vector search over test artifacts is a plus - Working knowledge of AI testing platforms (Healenium, Applitools, mabl, Testim) DevOps & Tooling - CI/CD with Jenkins or GitHub Actions - Docker and Kubernetes fundamentals - Test management (Jira/Xray, TestRail, or Zephyr) - Observability tools (Grafana, Prometheus, ELK) for test and pipeline diagnostics Technical Mentorship • Strong ability to mentor engineers through technical guidance and code reviews • Clear communication with engineering, product, and leadership stakeholders • Data-driven decision-making on quality and release readiness Preferred - Background in cybersecurity — vulnerability management, Policy Compliance - Experience testing multi-tenant SaaS at large data volumes. - Open-source contributions to testing or automation projects.