Lead QA Engineer

About this role

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.