Lead AI Engineer

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 tomorrows health today we want to hear from you.

Our 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.

The Lead AI Engineer provides technical leadership and architecture ownership for the companys 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.

Success 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 roles influence on AI platform decisions across the organization.

• AI Architecture Leadership: Define the technical architecture and roadmap for LLM/agentic systems model routing across cloud AI platforms connector/integration patterns RAG pipelines and prompt/evaluation frameworks.

• Solution Design & Governance: Lead architecture reviews for new AI capabilities and ensure designs meet enterprise security privacy and data-provenance requirements.

• Platform 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.

• Hands-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.

• Technical Mentorship: Set coding architecture and evaluation standards for Senior and Associate AI Engineers; run design reviews and pair on complex agentic workflows.

• LLMOps & Responsible AI: Establish secure observable and cost-attributed AI operations usage/spend attribution abuse monitoring model evaluation and rollback strategy for production LLM systems.

• Cross-Functional Architecture: Partner with engineering managers product platform and Legal/Compliance to align AI architecture decisions with delivery timelines and enterprise standards.

• Vendor & Model Strategy: Evaluate foundation model providers and AI tooling vendors; make build-vs-buy and model-selection recommendations.

• Compliance & Risk: Ensure AI systems handling protected health information (PHI) meet regulatory and enterprise governance requirements.

• Organizational Impact: Represent AI architecture in cross-company forums and influence enterprise-wide AI platform direction.

Priority will be given to candidates who reside in the Columbus OH metropolitan area.

We are unable to provide sponsorship for this role presently or in the future.

• Bachelors degree or equivalent experience; typically 8 years of software engineering experience including 3 years focused on AI/ML LLM or NLP systems in production. Fewer years required with a relevant Masters or Doctorate.

• One level of demonstrated technical leadership above a Senior AI Engineer e.g. owning architecture for a team or platform area not just a single feature.

• Deep hands-on expertise building production LLM applications: prompt engineering RAG/GraphRAG agentic workflows tool use and evaluation harnesses.

• Experience with commercial large language model APIs (e.g. Anthropic OpenAI) and tool-integration protocols such as Model Context Protocol (MCP).

• Strong software engineering fundamentals: Python and/or Java REST APIs event-driven architecture microservices and cloud-native design (Azure preferred; AWS/GCP acceptable).

• Experience with vector/graph retrieval systems embeddings and knowledge-base architectures at production scale.

• Working knowledge of LLMOps/MLOps: usage attribution cost/spend monitoring abuse detection and model evaluation pipelines.

• Ability to set architectural standards and mentor other engineers through design review and pairing not just documentation.

• Familiarity with regulated/healthcare data environments and AI governance frameworks (model risk review connector approval tiers PHI handling) is a plus.

• Advanced degree (M.S. or higher) in Computer Science AI/ML or a related technical field.

• Prior experience leading AI/ML platform or applied-AI teams inside healthcare IT or another highly regulated industry.

• Experience modernizing legacy systems toward AI-embedded workflows (agent-assisted development AI-powered risk scoring AI-driven automation).

• Experience with Confluence/Jira-based engineering governance and enterprise architecture review boards.

• Strong awareness of the fast-moving GenAI/agentic landscape and a demonstrated habit of continuous learning.

• Experience managing relationships with AI tooling vendors and model providers.

Clear written and verbal communication for both technical and executive audiences

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors including performance experience and skills equity regular job market evaluations and geographical markets. The pay range shown below is aligned with McKessons pay philosophy and pay will always be compliant with any applicable regulations. In addition to base pay other compensation such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson pleaseclick here.

Our Base Pay Range for this position

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McKesson is an Equal Opportunity Employer

McKesson provides equal employment opportunities to applicants and employees without regard to race color religion sex sexual orientation gender identity national origin protected veteran status disability age genetic information or any other legally protected category. For additional information on McKessons full Equal Employment Opportunity policies visit our Equal Employment Opportunity page.

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