Lead AI Engineer

Job description

Conceptual Proactive Problem-Solver Strategic Technologically Savvy Visual Thinker <meta data-json="{"ModuleType":13,"ApplyButtonText":"Apply","JobDetailsAlign":0,"JobDetailsDate":0,"JobDetailsJobTypeId":1,"JobDetailsSelectedDate":"2026-10-27T14:33:40.358Z","JobDetailsJobDateFormat":0,"JobDetailsJobLabelId":"Job ID","JobDetailsJobDatePosting":"Date posted","JobDetailsDescriptionFormat":0,"ShowApplyLater":false,"ShowApplyMobile":true,"ShowApplyLaterMobile":false,"ShowApplyLaterWeb":false,"ApplyLaterText":"Apply Later","ApplyLaterAlign":0,"ApplyLaterSubject":"[[JOB_TITLE]] at [[COMPANY_NAME]]","PublishedCandidateCardPageId":null,"ReferrerPageId":null,"ReferrerPageButtonText":"","ShowSavedJobsIcon":false,"IconLabel":"Save for Later","OverrideCandidateCard":false,"ModulePageType":2,"ModulePageName":"AJD - Design 1","DisplayJobDateFormat":"MM/dd/yyyy","JobDetailsSelectedId":"JR0155982","ApplyUrl":"https://mckesson.wd3.myworkdayjobs.com/External_Careers/job/USA-OH-Columbus/Lead-AI-Engineer_JR0155982-1/apply","JobDescription":"\u003Cp style=\u0022text-align:left\u0022\u003EMcKesson 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 \u2013 we care.\u003C/p\u003E\u003Cp style=\u0022text-align:inherit\u0022\u003E\u003C/p\u003E\u003Cp style=\u0022text-align:left\u0022\u003EWhat 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\u2019s health today, we want to hear from you.\u003C/p\u003E\u003Cp style=\u0022text-align:inherit\u0022\u003E\u003C/p\u003E\u003Cp style=\u0022text-align:inherit\u0022\u003E\u003C/p\u003E\u003Ch1\u003E\u003Cspan style=\u0022color:#1f3864\u0022\u003E\u003Cb\u003EAbout the Team\u003C/b\u003E\u003C/span\u003E\u003C/h1\u003E\u003Cp\u003EOur AI Enablement team drives enterprise-wide adoption of generative AI, spanning platform engineering, governance, and hands-on delivery of AI-powered products and internal tooling. The team builds and operates the infrastructure, integrations, and knowledge systems that let engineering and business teams safely adopt large language models at scale. The Lead AI Engineer joins as the senior technical authority on this team, setting the architectural direction that Senior and Associate AI Engineers build against.\u003C/p\u003E\u003Cbr /\u003E\u003Ch1\u003E\u003Cspan style=\u0022color:#1f3864\u0022\u003E\u003Cb\u003EPosition Summary\u003C/b\u003E\u003C/span\u003E\u003C/h1\u003E\u003Cp\u003EThe Lead AI Engineer provides technical leadership and architecture ownership for the company\u0027s AI platform and its embedded delivery initiatives, operating one level above the Senior AI Engineer role. This person owns the technical design of agentic and LLM-powered systems built on large language model APIs, including retrieval-augmented generation (RAG), tool/connector integration, and evaluation/governance tooling, in a highly regulated healthcare environment. The Lead AI Engineer sets architectural standards across AI-embedded product delivery, mentors Senior and Associate AI Engineers, and represents AI platform architecture to engineering leadership and Legal/Compliance/Privacy.\u003C/p\u003E\u003Cp\u003ESuccess is measured by the reliability, security, and scalability of the AI systems shipped, the rate at which Senior/Associate engineers adopt the architectural standards this role sets, and this role\u0027s influence on AI platform decisions across the organization.\u003C/p\u003E\u003Cbr /\u003E\u003Ch1\u003E\u003Cspan style=\u0022color:#1f3864\u0022\u003E\u003Cb\u003EKey Responsibilities\u003C/b\u003E\u003C/span\u003E\u003C/h1\u003E\u003Cul\u003E\u003Cli\u003EAI Architecture Leadership: Define the technical architecture and roadmap for LLM/agentic systems \u2014 model routing across cloud AI platforms, connector/integration patterns, RAG pipelines, and prompt/evaluation frameworks.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ESolution Design \u0026 Governance: Lead architecture reviews for new AI capabilities and ensure designs meet enterprise security, privacy, and data-provenance requirements.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EPlatform Ownership: Drive the technical design of shared AI platform capabilities, including knowledge-retrieval systems, citation/traceability of AI-generated outputs, and permission-aware access to data.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EHands-On Delivery: Personally architect and build high-complexity components on priority AI delivery initiatives where a working system, not just a design doc, is the deliverable.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ETechnical Mentorship: Set coding, architecture, and evaluation standards for Senior and Associate AI Engineers; run design reviews and pair on complex agentic workflows.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ELLMOps \u0026 Responsible AI: Establish secure, observable, and cost-attributed AI operations \u2014 usage/spend attribution, abuse monitoring, model evaluation, and rollback strategy \u2014 for production LLM systems.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ECross-Functional Architecture: Partner with engineering managers, product, platform, and Legal/Compliance to align AI architecture decisions with delivery timelines and enterprise standards.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EVendor \u0026 Model Strategy: Evaluate foundation model providers and AI tooling vendors; make build-vs-buy and model-selection recommendations.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003ECompliance \u0026 Risk: Ensure AI systems handling protected health information (PHI) meet regulatory and enterprise governance requirements.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EOrganizational Impact: Represent AI architecture in cross-company forums and influence enterprise-wide AI platform direction.\u003C/li\u003E\u003C/ul\u003E\u003Cbr /\u003E\u003Cp\u003E\u003Cb\u003E\u003Cu\u003EPriority will be given to candidates who reside in the Columbus, OH metropolitan area.\u003C/u\u003E\u003C/b\u003E\u003C/p\u003E\u003Cp\u003E\u003Cb\u003E\u003Cu\u003E\u003Cbr /\u003E\u003C/u\u003E\u003C/b\u003E\u003C/p\u003E\u003Cp\u003E\u003Cb\u003E\u003Cu\u003EWe are unable to provide sponsorship for this role, presently or in the future. \u003C/u\u003E\u003C/b\u003E\u003C/p\u003E\u003Cbr /\u003E\u003Ch1\u003E\u003Cspan style=\u0022color:#1f3864\u0022\u003E\u003Cb\u003EMinimum Requirements\u003C/b\u003E\u003C/span\u003E\u003C/h1\u003E\u003Cul\u003E\u003Cli\u003EBachelor\u0027s degree or equivalent experience; typically 8\u002B years of software engineering experience, including 3\u002B years focused on AI/ML, LLM, or NLP systems in production. Fewer years required with a relevant Master\u0027s or Doctorate.\u003C/li\u003E\u003C/ul\u003E\u003Cp\u003E\u003Cbr /\u003E\u003Cbr /\u003E\u003C/p\u003E\u003Ch1\u003E\u003Cspan style=\u0022color:#1f3864\u0022\u003E\u003Cb\u003ECritical Skills\u003C/b\u003E\u003C/span\u003E\u003C/h1\u003E\u003Cul\u003E\u003Cli\u003EOne level of demonstrated technical leadership above a Senior AI Engineer \u2014 e.g., owning architecture for a team or platform area, not just a single feature.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EDeep, hands-on expertise building production LLM applications: prompt engineering, RAG/GraphRAG, agentic workflows, tool use, and evaluation harnesses.\u003C/li\u003E\u003C/ul\u003E\u003Cul\u003E\u003Cli\u003EExperience with commercial large language model APIs (e.g., Anthropic, OpenAI) and tool-integration protocols suc