Principal AI Engineer

McKesson

. Own the multi-year technical strategy and roadmap for the enterprise AI platform across all teams .

Posted 10/27/2026full-timeRemote • Ohio • United StatesLead💰 $195,000 - $325,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in AI platform strategy, technical leadership, and architecture across multiple teams, with a strong focus on LLM applications and AI governance in regulated environments. Proven ability to influence stakeholders and shape enterprise-wide policies while managing complex AI initiatives.

Highest-signal resume keywords

AI Platform StrategyTechnical LeadershipProduction LLM ApplicationsAI Governance FrameworksCloud-Native Design

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

PythonJavaREST APIsEvent-Driven ArchitectureMicroservicesLLMOpsModel Evaluation PipelinesPrompt EngineeringVector Retrieval SystemsKnowledge-Base Architectures

Soft Skills

Exceptional Written CommunicationExceptional Verbal CommunicationInfluencing Stakeholders

Tools & Technologies

AzureAWSGCPCommercial LLM APIsModel Context Protocol

Industry Keywords

Healthcare ITRegulated Data EnvironmentsAI GovernanceModel Risk ReviewPHI Handling

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformJavaMicroservicesPython

About the role

Key responsibilities & impact

Own the multi-year technical strategy and roadmap for the enterprise AI platform across all teams
Set model strategy, RAG/retrieval architecture, connector ecosystems, and evaluation frameworks
Serve as the final technical escalation point for complex architecture and reliability problems across multiple teams and systems
Set, audit, and evolve architecture, security, and evaluation standards
Advise VP- and executive-level leadership on AI platform strategy, model risk, and investment trade-offs
Lead architecture and prototyping for the highest-ambiguity, highest-risk AI initiatives
Develop Lead and Senior AI Engineers through design reviews, technical coaching, and structured knowledge-sharing
Shape enterprise-wide AI governance policy with Legal, Compliance, and Privacy leadership
Own evaluation and long-term strategy for foundation model providers and AI infrastructure vendors
Represent McKesson’s AI engineering capability in industry forums, partner/vendor relationships, and senior technical recruiting
Influence AI platform direction and investment across the broader enterprise

Requirements

What you’ll need

Bachelor's degree or equivalent experience; fewer years required with a relevant Master's or Doctorate
Typically 12+ years of software engineering experience
6+ years focused on AI/ML, LLM, or NLP systems in production
3+ years operating as a senior individual-contributor technical leader
Technical leadership above a Lead AI Engineer across multiple teams
Experience setting technical strategy adopted by multiple teams
Hands-on expertise building production LLM applications at scale, including prompt engineering, RAG, agentic workflows, tool use, and evaluation harnesses
Experience with commercial LLM APIs such as Anthropic and OpenAI
Experience with tool-integration protocols such as Model Context Protocol (MCP)
Proficiency in 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
Deep working knowledge of LLMOps/MLOps, usage attribution, cost/spend monitoring, abuse detection, and model evaluation pipelines
Ability to influence senior engineering and executive stakeholders without direct authority
Familiarity with regulated/healthcare data environments and AI governance frameworks, including model risk review, connector approval tiers, and PHI handling
Preferred: advanced degree in Computer Science, AI/ML, or related technical field
Preferred: Principal, Staff, or Distinguished Engineer experience setting AI/ML strategy across multiple teams in healthcare IT or another highly regulated industry
Track record of publications, patents, open-source contributions, or industry speaking on applied AI/LLM systems preferred
Experience shaping enterprise-wide AI governance policy preferred
Awareness of the GenAI/agentic landscape and ability to distinguish durable technical bets from hype
Experience managing strategic relationships with AI infrastructure vendors and model providers
Exceptional written and verbal communication for executive, board-level, and external technical audiences
Must reside in the United States; sponsorship is unavailable presently or in the future

Benefits

Comp & perks

Competitive compensation package
Annual bonus may be offered
Long-term incentive opportunities may be offered
Benefits through McKesson’s Total Rewards program
Equal employment opportunities
Reasonable accommodation for applicants with disabilities