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Salary
≈ $18k – $44k per year (Estimated)
Location
In office (Pune)
Seniority
Staff · 5+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 9, 2026. First seen by Alion on Oct 7, 2026.

Overview
Company
Impact
Profile match
Qualys is an American security company founded in 1999 that pioneered delivering vulnerability scanning as a cloud service rather than as software customers installed and ran themselves. Its platform builds an inventory of an organisation's assets, scans them for vulnerabilities and misconfigurations, prioritises what to fix based on whether an exploit exists and is being used, and increasingly handles the patching itself. Headquartered in Foster City and listed on Nasdaq, it competes with Tenable and Rapid7 and has extended into cloud security posture management and compliance reporting.

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 a platform that ingests assets, findings, and risk signals from dozens of third-party security vendors ore - and normalizes them into a single risk model used by thousands of enterprise customers.

You will lead a team of QA and automation engineers, define the test strategy across UI, backend, and data pipelines, and drive our move toward AI-assisted, self-healing automation. This is a hands-on leadership role: you set direction, make release-quality calls, and still write and review framework code. Candidates who have built or meaningfully enhanced AI-based self-healing automation tools will stand out.

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Responsibilities

QA Leadership & Strategy

- Lead, mentor, and grow a team of 4-8 QA and automation engineers; run hiring, goal-setting, code reviews, and career development.

- Define and own the end-to-end test strategy for connector and platform releases - test planning, risk assessment, coverage targets, and entry/exit criteria.

- Act as the quality voice in sprint planning, design reviews, and release readiness; make clear go/no-go recommendations backed by data.

- Establish QA processes that scale: 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/GraphQL APIs, and Kafka-based pipelines.

- Build resilient UI automation with Playwright or Selenium 4, including parallel execution and reliable test data management.

- Own API and contract testing (REST Assured, Pact, Postman/Newman) covering OAuth2, JWT, token, and Basic auth flows, pagination, throttling, and vendor error handling.

- Validate data end-to-end: ingestion → normalization → PostgreSQL persistence → aggregation → UI, including schema and migration regression.

- Build mock vendor APIs and record-replay harnesses so connector tests run without live third-party credentials.

- 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.

- Introduce risk-based and change-impact test selection so CI runs the tests most relevant to each change.

- Evaluate AI testing tools (Healenium, Applitools, mabl, Testim, or in-house builds) and decide build-vs-buy based on accuracy, cost, and maintainability.

- Set guardrails for AI use in QA - validating AI-generated tests, measuring healing accuracy, and preventing false passes.

Qualifications

Experience

- 5-8 years in QA / test engineering, with at least 2 years leading or mentoring a QA team.

- 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 - and the ability to explain how you measured its impact.

Skills

**Automation & Testing**

- Playwright and/or Selenium 4; TestNG or JUnit 5; Cypress, Jest, or Vitest

- API automation: REST Assured, Postman/Newman, GraphQL testing, 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**

- Strong **Java** (17+) and **JavaScript/TypeScript**; Python is a plus

- SQL and data validation on PostgreSQL or similar

- Familiarity with microservices, Spring Boot, and Kafka or other event streaming systems

**AI & Machine Learning in QA**

- Self-healing locator strategies and ML-based 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

**Leadership**

- Test strategy and planning for complex, multi-component releases

- People leadership: hiring, mentoring, performance feedback

- Clear communication with engineering, product, and leadership stakeholders

- Data-driven decision-making on quality and release readiness

Preferred

- Background in cybersecurity - vulnerability management, CSPM, EDR, SIEM, or identity.

- Experience testing multi-tenant SaaS at large data volumes.

- ISTQB Advanced / Test Manager certification.

- Open-source contributions to testing or automation projects.

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