Lead AI Engineer

Location: Hybrid; position based in Columbus, Ohio, with other listed locations in Atlanta, Alpharetta, and USA Remote. Priority is given to candidates residing in the Columbus, Ohio metropolitan area. Visa sponsorship is unavailable now or in the future.

Base pay range: $155,300–$258,800 per year, plus potential annual bonus or long-term incentive opportunities.

Company

hirify.global is part of McKesson, a Fortune 10 healthcare company delivering products, services, and insights that improve access to quality care.

What you will do

• Define architecture and roadmaps for LLM and agentic systems, including model routing, connector integrations, RAG pipelines, and prompt and evaluation frameworks.
• Lead architecture reviews and ensure AI designs satisfy enterprise security, privacy, data-provenance, governance, and PHI-handling requirements.
• Design and build shared AI platform capabilities such as knowledge retrieval, citation and traceability, and permission-aware data access.
• Architect and implement high-complexity components for priority AI delivery initiatives.
• Set coding, architecture, and evaluation standards; mentor Senior and Associate AI Engineers through design reviews and pairing.
• Establish secure and observable LLMOps practices covering usage and spend attribution, abuse monitoring, model evaluation, rollback, vendor assessment, and cross-functional architecture decisions.

Requirements

• Bachelor's degree or equivalent experience, typically with 8+ years of software engineering experience, including 3+ years focused on AI/ML, LLM, or NLP systems in production. Fewer years may be accepted with a relevant master's degree or doctorate.
• Demonstrated technical leadership above the Senior AI Engineer level, including ownership of architecture for a team or platform area.
• Deep hands-on experience building production LLM applications using prompt engineering, RAG or GraphRAG, 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.
• Strong software engineering fundamentals with Python and/or Java, REST APIs, event-driven architecture, microservices, and cloud-native design; Azure is preferred, while AWS or GCP is acceptable.
• Production-scale experience with vector or graph retrieval systems, embeddings, and knowledge-base architectures.
• Working knowledge of LLMOps or MLOps, including usage attribution, cost and spend monitoring, abuse detection, and model evaluation pipelines.
• Ability to establish architectural standards and mentor engineers through design reviews and pairing.
• Clear written and verbal communication for technical and executive audiences.

Nice to have

• Familiarity with regulated or healthcare data environments and AI governance frameworks, including model risk review, connector approval tiers, and PHI handling.
• Advanced degree in Computer Science, AI/ML, or a related technical field.
• Experience leading AI/ML platform or applied-AI teams in healthcare IT or another highly regulated industry.
• Experience modernizing legacy systems toward AI-embedded workflows, including agent-assisted development, AI-powered risk scoring, or AI-driven automation.
• Experience with Confluence/Jira-based engineering governance and enterprise architecture review boards.
• Awareness of the fast-moving GenAI and agentic landscape, continuous learning, and experience managing relationships with AI tooling vendors and model providers.

Culture & Benefits

• Work in an impact-driven healthcare environment focused on improving access to quality care.
• Collaborate across engineering, product, platform, Legal, Compliance, and Privacy functions.
• Receive a competitive compensation package based on performance, experience, skills, equity, market evaluations, and geographic market.
• Potential eligibility for annual bonuses and long-term incentive opportunities.
• Equal employment opportunity and reasonable accommodation support are provided.