Lead QA Automation Engineer

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.
• Implement effective test data strategies, including synthetic data generation and environment setup.
• Integrate automated tests into CI/CD pipelines to support fast and reliable feedback cycles.
• Leverage AI‑assisted development tools (e.g., 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
• 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.
• Test Retrieval‑Augmented Generation (RAG) pipelines, including:
• Embedding quality validation
• Retrieval accuracy, recall, and relevance
• Chunking and indexing strategies
• 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.
• Critically evaluate AI‑generated suggestions and outputs to ensure accuracy, safety, reproducibility, and regulatory compli

Benefits

Additional Information

About McKesson Compile Established in 1833, McKesson is a US Fortune 10 global leader in healthcare supply chain management solutions, retail pharmacy, healthcare technology, community oncology, and specialty care. We partner with life sciences companies, manufacturers, providers, pharmacies, governments, and other healthcare organizations to help provide the right medicines, medical products, and healthcare services to the right patients at the right time, safely and cost effectively. Based in Bangalore India, McKesson Compile's data is a comprehensive, full linked system of record for the US Healthcare market, with intelligence on 2M+ healthcare professionals (HCPs) and over 800K facilities. Compile's data includes high capture medical and pharmacy claims, closed capture Medicare claims (100%), along with best-in-class provider affiliations and customer master. At McKesson we deliver careers with purpose and potential. Our focus on better health starts with creating an inclusive environment with strong values where you can build a fulfilling career. You can count on us to provide you with resources and opportunities to grow and be your best, while contributing to our pursuit of improving lives. Ontada is a leading oncology real‑ world data and evidence, clinical education, and provider technology business dedicated to transforming the fight against cancer. Part of McKesson Corporation, we support science through our data, technology, and channels, accelerating innovation for life science companies, empowering community oncology providers, and advancing patient care. Together with our partners, we improve the lives of cancer patients. Position Summary The Lead QA Automation Engineer is a senior individual contributor responsible for designing, developing, and maintaining automated test solutions across Ontada's product ecosystem, with a strong focus on AI-enabled and GenAI-powered systems. Reporting to the QA Manager, 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

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