Lead AI Engineer

Requirements:

• We seek a candidate with a bachelors degree or equivalent experience and typically 8+ years of software engineering experience, including 3+ years focused on production AI/ML, LLM, or NLP systems. Fewer years may be required with a relevant masters or doctoral degree.
• We require demonstrated technical leadership beyond the Senior AI Engineer level, such as owning architecture for a team or platform area.
• We seek deep hands-on experience building production LLM applications, including prompt engineering, RAG or GraphRAG, agentic workflows, tool use, and evaluation harnesses.
• We require experience with commercial LLM APIs, such as Anthropic or OpenAI, and tool-integration protocols such as Model Context Protocol (MCP).
• We require strong software engineering fundamentals, including Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design. Azure is preferred; AWS or GCP experience is also acceptable.
• We seek experience with vector or graph retrieval systems, embeddings, and production-scale knowledge-base architectures.
• We require working knowledge of LLMOps or MLOps, including usage attribution, cost monitoring, abuse detection, and model-evaluation pipelines.
• We require the ability to establish architectural standards and mentor engineers through design reviews and pairing.
• Familiarity with regulated or healthcare data environments and AI governance frameworks, including model risk review, connector approval tiers, and PHI handling, is a plus.
• We prefer an advanced degree in Computer Science, AI/ML, or a related technical field.
• We prefer experience leading AI/ML platform or applied-AI teams in healthcare IT or another highly regulated industry.
• We value experience modernizing legacy systems toward AI-embedded workflows, such as agent-assisted development, AI-powered risk scoring, or AI-driven automation.
• We value experience with Confluence/Jira-based engineering governance and enterprise architecture review boards.
• We seek strong awareness of the evolving GenAI and agentic landscape, a habit of continuous learning, and experience managing relationships with AI tooling vendors and model providers.
• We require clear written and verbal communication for technical and executive audiences.

Responsibilities:

• We rely on this role to define the technical architecture and roadmap for LLM and agentic systems, including model routing, integrations, RAG pipelines, and prompt and evaluation frameworks.
• We expect this role to lead architecture reviews and ensure new AI capabilities meet enterprise security, privacy, and data-provenance requirements.
• We count on this role to guide shared AI platform capabilities, including knowledge retrieval, citation and traceability of AI-generated outputs, and permission-aware data access.
• We need this role to architect and build complex components for priority AI initiatives when implementation, not only design documentation, is required.
• We expect this role to set coding, architecture, and evaluation standards for Senior and Associate AI Engineers, lead design reviews, and pair on complex agentic workflows.
• We rely on this role to establish secure, observable, cost-attributed AI operations, including usage and spend attribution, abuse monitoring, model evaluation, and rollback strategies for production LLM systems.
• We expect this role to partner with engineering managers, product, platform, and Legal, Compliance, and Privacy teams to align architecture with delivery timelines and enterprise standards.
• We need this role to evaluate foundation-model providers and AI tooling vendors and recommend build-versus-buy approaches and model selections.
• We expect this role to ensure AI systems handling protected health information meet regulatory and enterprise governance requirements.
• We rely on this role to represent AI architecture in cross-company forums and influence our enterprise-wide AI platform direction.

Technologies:

• AI
• AWS
• Architect
• Azure
• Cloud
• Confluence
• Embedded
• GCP
• JIRA
• Java
• LLM
• MCP
• MLOps
• Python
• RAG
• REST
• Security
• microservices

More

We are McKesson, an impact-driven Fortune 10 healthcare company delivering insights, products, and services intended to make quality care more accessible and affordable. Our culture supports growth, new ideas, and meaningful impact. Our AI Enablement team advances enterprise adoption of generative AI through platform engineering, governance, and delivery of AI-powered products and internal tools. This Lead AI Engineer is the teams senior technical authority, guiding architecture for our AI platform and embedded delivery initiatives in a regulated healthcare environment. We prioritize candidates in the Columbus, Ohio metropolitan area and are unable to provide sponsorship now or in the future. We offer a competitive total rewards package, with a base pay range of $155,300–$258,800; additional compensation, such as an annual bonus or long-term incentives, may also be available. We are an equal opportunity employer and provide equal employment opportunities to applicants and employees.

last updated 43 week of 2026