Senior QA Engineer

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 Senior QA Automation Engineer is an experienced individual contributor responsible for designing, developing, and maintaining automated test solutions across Ontada's product ecosystem, including AI-enabled and GenAI-powered applications. Reporting to the QA Manager, this role contributes to the quality, reliability, and scalability of web applications, APIs, backend services, and AI-driven workflows through effective quality engineering practices and automation.

This role partners closely with Product, Engineering, and Operations teams to validate traditional software capabilities as well as emerging AI-enabled features, including prompt-driven workflows, Retrieval-Augmented Generation (RAG) solutions, and model-integrated services.

Key Responsibilities

Quality Engineering Ownership & Execution

• Own test planning and execution for assigned features, modules, and services.
• Identify functional, integration, performance, and quality risks and escalate concerns proactively.
• Create and maintain test plans, test cases, and traceability documentation aligned with product requirements.
• Execute exploratory testing to uncover complex workflows and edge-case defects.
• Support release validation activities and ensure quality readiness for production deployments.
• Participate in root-cause investigation and defect triage activities.

Test Automation & Framework Development

• Contribute to automation framework enhancements to improve scalability, maintainability, and test coverage.
• Develop reusable test utilities and automation components.
• Support code reviews and automation best practices within the QA team.

AI / GenAI Quality Engineering

• Design and execute test scenarios for AI-enabled and GenAI-powered applications.
• Validate prompt behavior, prompt templates, and AI-assisted workflows across multiple test scenarios.
• Perform testing for AI-related failure modes, including hallucinations, prompt injection attempts, response inconsistencies, and unsafe outputs.
• Validate AI-generated responses for relevance, accuracy, consistency, and reliability.
• Participate in testing Retrieval-Augmented Generation (RAG) implementations, including retrieval quality and response grounding.
• Collaborate with engineering teams to verify model configurations, integrations, and inference workflows.
• Utilize AI-powered tools to improve test design, test automation development, and exploratory testing.

Backend & Data Testing

• Perform backend testing using SQL and NoSQL databases.
• Validate data ingestion, transformation, persistence, and integrity across systems.
• Test API integrations, messaging workflows, and asynchronous processing pipelines.
• Investigate data-related production defects and support root-cause analysis.

Agile Collaboration

• Collaborate with developers early in the development lifecycle to improve testability and automation coverage.
• Provide QA estimates and testing input during sprint planning and backlog refinement.
• Guide junior team members on automation best practices when required.

Quality Governance, Compliance & Continuous Improvement

• Ensure testing activities comply with healthcare, security, privacy, and regulatory requirements.
• Maintain audit-ready documentation including test evidence and validation reports.
• Contribute to continuous improvement initiatives across QA processes, tooling, and automation practices.

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

• 4+ years of Software Quality Assurance experience.
• 3+ years of hands-on automation development experience.
• 3+ years of API testing and automation experience.
• 3+ years of backend and database testing experience using SQL.
• Strong hands-on experience with Selenium, Playwright, Cypress, TOSCA, or comparable automation tools.
• Proficiency in Java, Python, or JavaScript.
• Experience working within Agile development environments.
• Experience with CI/CD pipelines and tools such as Jenkins, GitHub Actions, or GitLab CI.
• Understanding of microservices-based architectures and API-driven systems.
• Experience using source control systems such as GitHub or Bitbucket.
• Solid understanding of software testing methodologies, automation frameworks, and quality engineering best practices.
• Exposure to AI-assisted engineering tools such as GitHub Copilot, Claude Code, or similar.

Additional Skills

• Experience testing AI-enabled, GenAI, or LLM-powered applications.
• Exposure to prompt testing and AI workflow validation.
• Familiarity with RAG concepts and semantic search.
• Experience with SQL and NoSQL databases.
• Knowledge of cloud platforms such as Azure, AWS, or GCP.
• Experience using performance testing tools such as JMeter, NeoLoad, or similar.
• Knowledge of healthcare or regulated industry environments.

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 .