Principal AI Engineer

Location: Fully remote in the United States, with priority given to candidates residing in the Columbus, Ohio metropolitan area.

Base pay: $195,000–$325,000 per year, with potential annual bonus and long-term incentive opportunities.

Company

McKesson is a Fortune 10 healthcare company delivering healthcare products, services, and insights.

What you will do

• Own the multi-year technical strategy and roadmap for the enterprise AI platform, including model strategy, RAG and retrieval architecture, connector ecosystems, and evaluation frameworks.
• Act as the final technical escalation point for complex architecture, reliability, security, and platform problems across multiple teams.
• Set and evolve architecture, security, evaluation, model risk, connector approval, and PHI-handling standards with Legal, Compliance, and Privacy leadership.
• Lead architecture and prototyping for high-ambiguity, high-risk AI initiatives and advise executive leadership on AI strategy, risk, and investment trade-offs.
• Mentor Lead and Senior AI Engineers through design reviews, technical coaching, and structured knowledge-sharing.
• Manage enterprise-level strategy for foundation-model providers and AI infrastructure vendors, while representing AI engineering externally.

Requirements

• Bachelor’s degree or equivalent experience, typically with 12+ years of software engineering experience, including 6+ years focused on AI/ML, LLM, or NLP systems in production and 3+ years as a senior individual-contributor technical leader; fewer years may be required with a relevant Master’s or Doctorate.
• Technical leadership above the Lead AI Engineer level, including setting direction and standards across multiple teams.
• Proven experience setting technical strategy adopted by multiple teams.
• Hands-on experience 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 or OpenAI and tool-integration protocols such as Model Context Protocol (MCP).
• Strong software engineering fundamentals with Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design; Azure is preferred, while AWS and GCP are acceptable.
• Experience with vector and graph retrieval systems, embeddings, and production-scale knowledge-base architectures across multiple products.
• Deep knowledge of LLMOps/MLOps, including usage attribution, cost monitoring, abuse detection, model evaluation pipelines, and designing these systems from scratch.
• Ability to influence senior engineering and executive stakeholders without direct authority, plus familiarity with regulated healthcare data and AI governance frameworks.

Nice to have

• Advanced degree in Computer Science, AI/ML, or a related technical field.
• Principal, Staff, or Distinguished Engineer experience setting AI/ML strategy across multiple teams in healthcare IT or another highly regulated industry.
• Publications, patents, open-source contributions, or industry speaking on applied AI/LLM systems.
• Experience shaping enterprise AI governance policy with Legal, Compliance, and Privacy leadership.

Culture & Benefits

• Fully remote work within the United States.
• Competitive compensation based on performance, experience, skills, equity, market evaluations, and geography.
• Potential annual bonus and long-term incentive opportunities in addition to base pay.
• Work in a regulated healthcare environment focused on responsible AI, patient well-being, and accessible care.
• Equal employment opportunity and reasonable accommodation support are provided.