Principal AI Engineer

This is a fully remote position, open to applicants in Ohio.

📋 Description

• Take ownership of the multi-year technical strategy and roadmap for McKesson's enterprise AI platform across all teams.

• Establish model strategy, RAG/retrieval architecture, connector ecosystems, and evaluation frameworks.

• Act as the ultimate technical escalation point for intricate architecture and reliability challenges.

• Define and enhance architecture, security, and evaluation standards across various teams.

• Provide guidance to VP- and executive-level leadership on AI platform strategy, model risk, and investment considerations.

• Lead the architecture and prototyping efforts for high-ambiguity, high-risk AI projects.

• Develop Lead and Senior AI Engineers through design reviews, coaching, and knowledge sharing.

• Shape the enterprise AI governance policy, including model risk review, connector/tool approvals, and PHI-handling standards.

• Oversee evaluation and long-term strategy for foundation model providers and AI infrastructure vendors.

• Represent McKesson's AI engineering capabilities in industry forums, partner/vendor relations, and senior technical recruitment.

• Influence the AI platform direction and investment strategies across the broader enterprise.

⛳️ Requirements

• 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 dedicated to AI/ML, LLM, or NLP systems in production settings.

• 3+ years functioning as a senior individual-contributor technical leader.

• Demonstrated technical leadership above a Lead AI Engineer across multiple teams.

• Proven history of establishing technical strategies embraced by multiple teams.

• Hands-on experience in developing production LLM applications at scale, including prompt engineering, RAG, agentic workflows, tool usage, and evaluation harnesses.

• Familiarity with commercial large language model APIs, such as Anthropic and OpenAI.

• Experience with tool-integration protocols, including Model Context Protocol (MCP).

• Strong foundation in software engineering principles: 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.

• In-depth knowledge of LLMOps/MLOps, including usage attribution, cost/spend monitoring, abuse detection, and model evaluation pipelines.

• Ability to influence and align senior engineering and executive stakeholders without direct authority.

• Familiarity with regulated/healthcare data environments and AI governance frameworks.

• Advanced degree in Computer Science, AI/ML, or a related technical field preferred.

• Previous experience as a Principal, Staff, or Distinguished Engineer establishing AI/ML technical strategy across multiple teams is preferred.

• Publications, patents, open-source contributions, or industry speaking engagements on applied AI/LLM systems are preferred.

• Experience shaping enterprise-wide AI governance policy is preferred.

• Awareness of the GenAI/agentic landscape.

• Experience managing strategic relationships with AI infrastructure vendors and model providers.

• Exceptional written and verbal communication skills for executive, board-level, and external technical audiences.

• Must reside in the United States; sponsorship is not available now or in the future.

🏝️ Benefits

• Competitive compensation package.

• Annual bonus or long-term incentive opportunities may be available.

• Equal employment opportunities.

• Reasonable accommodations for job search or application processes.