Principal Engineer (Healthcare)

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you.About the RoleWe are seeking a Principal Engineer to serve as a hands-on technical leader across the full breadth of our platform — data engineering, software engineering, and AI engineering. This is our most senior individual-contributor role and is reserved for engineers who combine deep technical mastery with organization-wide influence.The Principal Engineer sets technical direction, designs systems that operate reliably and securely at scale, and raises the engineering bar across teams. You will partner closely with engineering leadership, product management, and clinical and scientific stakeholders to solve the hardest problems in precision oncology — from large-scale genomic data pipelines to production AI/ML systems that support clinical and research decision-making. This position reports to the Sr. Director, Genospace Engineering.What You’ll Do (Responsibilities)Design cross-domain architecture — define end-to-end architecture for complex systems that span data pipelines, application services, and AI/ML workloads, balancing scalability, reliability, security, and cost.Lead data engineering at scale — design and deliver ingestion, transformation, storage, and governance for large volumes of genomic and clinical data, with strong data quality and lineage.Build production software across the stack — architect and implement robust services from back-end data stores through APIs to front-end experiences, with a keen sense for making things fast and efficient.Productionize AI/ML — design, develop, and deploy AI/ML and GenAI capabilities, and establish the MLOps foundations (training, evaluation, deployment, monitoring, and responsible-AI practices) that keep them dependable.Set the engineering bar — establish and champion standards for code quality, testing, security, scalability, and regulatory compliance (e.g., HIPAA / PHI handling).Drive technical strategy — shape multi-quarter technical roadmaps and make build/buy and platform decisions in partnership with engineering, product, and data-science leadership.Multiply the team — mentor senior and junior engineers, lead design and code reviews, and grow technical talent and best practices across the organization.Advance the state of the art — evaluate and introduce new technologies, frameworks, and practices where they create measurable improvement, and stay current with the evolving AI and d...