About the Role

Were looking for a Senior QA Automation Engineer who treats AI as a core part of how quality gets built, not an add-on.

Key Responsibilities

Automation Strategy & Architecture

- Design, build, and evolve scalable test automation frameworks across UI, API, mobile, and integration layers
- Define the test pyramid and quality gates for the organization, balancing speed, coverage, and reliability
- Embed automated quality checks into CI/CD pipelines with fast, trustworthy feedback loops
- Drive shift-left practices: partner with developers on testability, contract testing, and early validation

AI-Native Quality Engineering

- Use LLMs and AI coding assistants to generate test cases, test data, and automation scripts from requirements, user stories, and code changes
- Implement self-healing locators and AI-assisted test maintenance to reduce flakiness and upkeep cost
- Apply AI to triage failures, cluster defects, detect flaky tests, and identify root causes from logs and traces
- Build or integrate AI agents for exploratory testing, visual validation, and regression selection (risk-based test prioritization)
- Evaluate AI testing tools critically, deciding what to adopt, build, or avoid, and measure their actual ROI

Testing AI/ML-Powered Features

- Build golden datasets, regression suites, and automated evals for prompts, RAG pipelines, and agent workflows
- Test non-deterministic behavior using statistical thresholds, LLM-as-judge techniques, and human review loops
- Perform adversarial testing, including prompt injection, jailbreaks, and data leakage scenarios

Required Qualifications

Experience

- 8–10 years in QA/test automation, with at least 3 years in a senior or lead capacity




- Proven track record building automation frameworks from scratch and scaling them across teams

Technical Skills

- Strong programming ability in at least one of: Python, Java, TypeScript/JavaScript
- Hands-on with up-to-date automation tools: Playwright, Cypress, Selenium, Appium
- API and service testing: REST, GraphQL, gRPC (Postman, REST Assured, Pact, or similar)
- CI/CD experience: GitHub Actions, GitLab CI, Jenkins, or Azure DevOps
- Familiarity with containers, cloud environments (AWS/Azure/GCP), and infrastructure basics
- Solid understanding of performance, security, and accessibility testing fundamentals
- Strong SQL and data validation skills

AI-Native Skills

- Daily, fluent use of AI coding assistants (e.g., Claude, Copilot, Cursor) with strong prompting and output-verification habits
- Experience building workflows with LLM APIs, agents, or MCP-based tooling for testing tasks
- Understanding of LLM limitations: hallucination, non-determinism, context constraints, and data privacy risks

Preferred Qualifications

- Experience testing RAG systems, chatbots, or agentic applications in production
- Background in observability and test analytics (Datadog, Grafana, ELK)
- Experience with visual regression and AI-based visual testing tools
- Knowledge of responsible AI, governance, and compliance considerations
- Contributions to open-source testing tools or internal developer platforms
- ISTQB or relevant cloud/AI certifications

Soft Skills

- Sharp analytical thinking and healthy skepticism toward both code and AI output
- Clear communication with technical and non-technical stakeholders
- Ownership mindset and comfort with ambiguity in a fast-changing tooling landscape
- Curiosity and a bias toward experimentation, with the discipline to measure results

📌 Qa Automation Lead (Gurugram)
🏢 Bounteous
📍 Gurugram