07 Aug
|
Compile
|
Bengaluru
About McKesson Compile
The Senior QA Automation Engineer is an individual contributor responsible for designing, developing, and maintaining automated test solutions across Ontada s product ecosystem, with a solid focus on AI enabled and GenAI powered systems
Reporting to the QA Lead, this role drives high quality automation for UI, API, backend, and data layers, while ensuring AI/ML features meet expectations for correctness, reliability, safety, and compliance
This role partners closely with Product, Engineering, and Operation teams to validate both traditional software workflows and AI driven behaviors, including prompt based systems, retrieval augmented generation (RAG), and model integrated services
Key Responsibilities
Quality Engineering Ownership Execution
- Own and execute test strategy, planning, and execution for assigned features, services, or product areas
- Identify functional, integration, and non functional quality risks early; communicate risks, impacts, and recommendations clearly
- Author comprehensive test strategies, test plans, and test cases aligned with product requirements and acceptance criteria
- Perform exploratory testing to uncover complex, edge case, and systemic defects
- Coordinate end to end validation across multiple environments to ensure release readiness
Test Automation Framework Development
- Design, develop, and maintain automated test suites across UI, API, service, and data layers
- Contribute to the enhancement and maintainability of automation frameworks using tools such as Selenium, TOSCA, etc
- Develop robust API automation using RestAssured, Postman, or equivalent frameworks
- Apply practical test data strategies (eg, synthetic test data, environment setup) to improve test repeatability
- Integrate automated tests into CI/CD pipelines to support fast and reliable feedback cycles
- Leverage AI assisted development tools (eg, GitHub Copilot, Claude Code, or similar ) to accelerate test automation development, refactoring, and debugging while maintaining code quality and security standards
- Use AI tooling to assist with test case generation, edge case identification, and data driven scenario expansion , validating all outputs through engineering judgment and established QA practices
AI / GenAI Quality Engineering
- Exposure to agentic AI frameworks (eg, LangChain, google ADK, CrewAI, OpenAI Assistants, or similar) and understanding of agent/skills/task orchestration concepts
- Design, develop, and maintain AI agents to automate QA tasks, including test case generation, test execution, defect triage, and reporting
- Design and execute test strategies for AI/ML and GenAI powered features, including LLM based workflows
- Validate prompt behavior, prompt templates, and prompt chaining across different scenarios and data contexts
- Perform negative testing for AI systems,
including prompt injection, jailbreak attempts, hallucination risks, and unsafe outputs
- Validate AI outputs for accuracy, consistency, explainability, and compliance in regulated environments
- Collaborate with Engineering and Operations teams to test model integrations, configuration changes, and inference pipelines
- Utilize AI powered tools to support prompt analysis, test scenario exploration, and hypothesis generation when validating LLM based features and AI workflows
Backend Data Testing
- Perform backend testing using SQL and/or NoSQL data systems
- Validate data ingestion, transformations, persistence, and integrity across services and environments
- Assist with testing asynchronous workflows and integrations (eg, message queues, APIs, batch processes)
Agile Collaboration
- Work with Product Owners and Business Analysts to clarify user stories, define acceptance criteria, and improve testability
- Collaborate with developers during design and implementation to support shift left testing
- Participate in sprint ceremonies (planning, grooming, retrospectives) and provide timely QA status updates
- Coordinate with onshore/offshore team members to ensure consistent execution and defect follow up
Quality Governance, Compliance Continuous Improvement
- Contribute audit ready documentation, including test plans, execution evidence, and reports
- Participate in root cause discussions for quality issues and contribute to corrective actions
- Identify opportunities for improving QA processes, tools, and documentation; contribute suggestions through established continuous improvement channels
- Research and evaluate new QA, automation, or performance testing, AI assisted tools and techniques as appropriate
Minimum Requirement
Degree or equivalent and typically requires 4+ years of relevant experience
Education
Bachelor s degree in computer science, Engineering, Mathematics, or equivalent practical experience
Critical Skills
- 5+ years of progressive Software Quality Assurance experience, preferably in healthcare or regulated industries
- 3+ years of hands on test automation development experience
- 3+ years of API testing and automation experience
- 3+ years of backend testing experience using SQL and/or NoSQL databases
- 1+ years of experience testing AI/ML or GenAI systems or demonstrated delivery of AI adjacent quality frameworks (eg, prompt testing, RAG evaluation, guardrails)
- Experience owning QA execution for complex product areas with limited day to day oversight
- Experience mentoring or supporting junior QA engineers
- Strong experience working in Agile SDLC environments with CI/CD pipelines
- Proficiency in Java, JavaScript, or Python for test automation and scripting
- Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI and build tools like Maven or Gradle
- Solid understanding of QA methodologies, test design techniques, and quality metrics
- Experience using profiling and monitoring tools (Dynatrace, New Relic, AppDynamics, Splunk, JProfiler)
- Experience creating reusable, maintainable, and portable automation and performance test scripts
- RAG testing experience, including embedding quality, retrieval evaluation, and chunk strategy validation
- Familiarity with vector databases and semantic search concepts
- Hands on experience using AI assisted coding and analysis tools such as GitHub Copilot, Claude Code, or similar
- Ability to apply AI tools effectively for:
- Test automation development and refactoring
- Debugging and root cause investigation
- Exploratory test design and edge case discovery
Additional Skills
- Experience with source control tools such as GitHub, Bitbucket, Git Bash
- Experience with test management tools (qTest, TestRail, ALM, TestLink, or similar)
- Familiarity with microservices and distributed system architectures
- Knowledge of healthcare software, data privacy, and regulatory compliance is a plus
- Ability to manage multiple priorities and work independently in a fast paced environment
Working Conditions
- Full-time in office role based in Bangalore, India (IST)
- Collaboration with distributed, cross functional teams
McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages
In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application
McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail
Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates
McKesson job postings are posted on our career site: careers
mckesson
com
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
📌 Senior QA Automation Engineer (Bengaluru)
🏢 Compile
📍 Bengaluru