AI Engineer

McKesson•Richmond, VA

16d

About The Position

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow’s health today, we want to hear from you. We are seeking an experienced AI Developer/Engineer (Level 3) to design, develop, and deploy enterprise-grade generative AI solutions. This role requires deep expertise in modern AI application frameworks, cloud platforms, and the ability to work independently while collaborating across cross-functional teams. The ideal candidate will drive AI initiatives from concept through production, ensuring solutions meet security, compliance, and performance standards.

Requirements

5+ years of overall professional software engineering experience
3+ years of hands-on experience developing AI/ML or generative AI applications, including Production deployment of GenAI solutions (e.g., RAG, agentic workflows)
End-to-end SDLC ownership in enterprise environments
Demonstrated experience operating AI systems in secure, regulated, enterprise-scale environments
Bachelor’s degree in Business, Computer Science, Software Engineering, Data Science, Artificial Intelligence, or a related technical field, Master’s degree in a related field preferred
An equivalent combination of education, training, and relevant hands-on experience may be considered

Nice To Haves

Google Cloud – Professional Machine Learning Engineer
Google Cloud Generative AI Engineer (or equivalent GenAI specialization)
Google Cloud – Professional Cloud Architect

Responsibilities

Design, develop, and maintain generative AI applications utilizing RAG architectures, agentic workflows, and modern orchestration patterns
Architect and implement solutions using Azure and GCP services, including Vertex AI, Agent Builder, ADK, and Gemini foundation models
Build and optimize embedding pipelines and vector retrieval systems using best practices for semantic search and knowledge retrieval
Develop and integrate applications with enterprise orchestration platforms such as Salesforce AgentForce, Microsoft Copilot, and Snowflake Cortex AI
Lead AI projects through the complete software development lifecycle (SDLC), from requirements gathering to production deployment and monitoring
Design and implement prompt engineering strategies, including prompt versioning, management, and optimization for production systems
Implement LLM evaluation frameworks to measure response quality, accuracy, and relevance across AI applications
Implement AI observability mechanisms, define key performance indicators (KPIs), and establish monitoring dashboards for model performance and application health
Monitor and optimize LLM API costs and token usage to ensure cost-effective operation at scale
Ensure all AI solutions comply with enterprise security, privacy, and regulatory requirements
Collaborate with data engineering, platform, and business teams to deliver integrated AI solutions that meet organizational objectives
Provide technical guidance and mentorship to junior team members on AI development best practices
Evaluate emerging AI technologies and recommend adoption strategies aligned with business goals