Automation Software Engineering

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The Software Automation Engineer (P3) is a senior individual contributor responsible for designing, developing, and maintaining automated test solutions across Ontada's product ecosystem, with a strong focus on AIenabled and GenAIpowered systems. Reporting to the QA Lead, this role drives highquality 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 MLOps teams to validate both traditional software workflows and AIdriven behaviors, including promptbased systems, retrievalaugmented generation (RAG), and modelintegrated services.
Quality Engineering Ownership & Execution

Own and execute test strategy, planning, and execution for assigned features, services, or product areas under the guidance of the QA Lead.
Identify functional, integration, and nonfunctional quality risks early; communicate risks, impacts, and recommendations clearly.
Perform exploratory testing to uncover complex, edgecase, and systemic defects.
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, Playwright, Cypress, TOSCA, or similar.
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.
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, edgecase identification, and datadriven 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 GenAIpowered features, including LLMbased 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 RetrievalAugmented Generation (RAG) pipelines, including:
Embedding quality validation
Validate AI outputs for accuracy, consistency, explainability, and compliance in regulated environments.
Collaborate with Engineering and MLOps teams to test model integrations, configuration changes, and inference pipelines.
Utilize AIpowered tools to support prompt analysis, test scenario exploration, and hypothesis generation when validating LLMbased features and AI workflows.
Critically evaluate AIgenerated suggestions and outputs to ensure accuracy, safety, reproducibility, and regulatory compliance.
Backend & Data Testing

Perform advanced backend testing across SQL and NoSQL data systems.
Validate data ingestion, transformations, persistence, and integrity across services and environments.
Coordinate testing of asynchronous workflows and integrations (e.g., Agile Collaboration

Partner with developers during design and implementation to support shiftleft testing.
Collaborate with onshore and offshore QA team members to ensure consistent execution and quality standards.
Quality Governance, Compliance & Continuous Improvement

Ensure testing activities align with HIPAA and other regulatory, security, and dataprivacy requirements.
Participate in rootcause analysis for quality or performance issues and support corrective actions.
Research and evaluate new QA, automation, or performance testing, AI assisted tools and techniques as appropriate.
Bachelor's degree in computer science, Engineering, Mathematics, or equivalent practical experience.
4+ years of progressive Software Quality Assurance experience, preferably in healthcare or regulated industries.

• 3+ years of handson test automation development experience.
• 2+ years of API testing and automation experience.
• 3+ years of backend testing experience using SQL and/or NoSQL databases.
• 3+ years of software performance testing experience, including test planning, execution, and analysis.
• 1+ years of experience testing AI/ML or GenAI systems , or demonstrated delivery of AIadjacent quality frameworks (e.g., prompt testing, RAG evaluation, guardrails).
• 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.
Solid understanding of QA methodologies, test design techniques, and quality metrics.
Handson experience with performance testing tools (JMeter, NeoLoad, or similar).
Experience using profiling and monitoring tools (Dynatrace, New Relic, AppDynamics, Splunk, JProfiler).
Ability to analyze performance issues related to CPU, memory/heap, garbage collection, threads, databases, messaging systems, and network latency.
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.
Handson experience using AIassisted coding and analysis tools such as GitHub Copilot, Claude Code, or similar .
Ability to apply AI tools effectively for:
Test automation development and refactoring
Strong understanding of limitations and risks of AIgenerated outputs , with the ability to validate, correct, and harden results for productionquality use.
Experience benchmarking, capacity planning, and release readiness reporting.
Knowledge of healthcare software, data privacy, and regulatory compliance is a plus.
Fully remote role within the Eastern or Central United States.
This position offers the possibility of a hybrid work arrangement based on recent updates to our in-office/workfromhome model. If located in DFW area, the selected candidate may be expected to work onsite at our Las Colinas office a minimum of two (2) days per week, with the remaining days worked remotely. S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role.
Applicants must be currently authorized to work in the United States on a fulltime basis without the need for employer support or sponsorship now or in the future. This includes having the legal right to work in the United States without the need for McKesson support or sponsorship for any immigration related employment authorization (e.g., H1B, O1, E3, H1B1, TN, F1 OPT, F1 STEM OPT, F1 CPT, etc.) If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position
This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. 106,100 - $176,800 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. 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.
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