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.
McKesson is in the business of better health, and we touch the lives of patients in virtually every aspect of healthcare. We partner with payors, hospitals, physician offices, pharmacies, pharmaceutical companies, and others across the spectrum of care to build healthier organizations that deliver better care to patients in every setting. We believe in the importance of strong, vital organizations because we know that patients can only be healthy when our system is healthy.
Every single McKesson employee contributes to our mission—by joining McKesson you act as a catalyst in a chain of events that helps millions of people all over the globe. Talented, compassionate people are the future of our company—and of healthcare. At McKesson, you’ll collaborate on the products and solutions that help us carry out our mission to improve lives and advance healthcare. Working here is your opportunity to shape an industry that’s vital to us all.

POSITION DESCRIPTION

We are seeking a highly skilled and experienced Lead Architect to join our dynamic team on Automation and Agentic AI. The successful candidate will play a crucial role in spearheading our AI-driven process automation initiatives, utilizing their expertise in Microsoft Azure to drive innovation and efficiency.

MINIMUM REQUIREMENTS

Typically requires 10+ years of relevant experience.

CRITICAL SKILLS

• Over 10 years of experience developing automation products utilizing technologies such as RPA, machine learning, NLP, cognitive solutions, chatbots
• Experience building autonomous systems or tools that use memory, reasoning, or planning
• Deep understanding of agentic AI principles, reinforcement learning, and cognitive architectures
• Hands-on experience with Microsoft Copilot Studio platform, including agent development and deployment
• Rapid prototyping, experimentation, and staying on the frontier of AI advancements.
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Thorough understanding of how to assess, evaluate, and integrate AI tools
• Proven ability to lead AI and automation projects from concept to production

ADDITIONAL SKILLS

• Proven ability to develop and deliver comprehensive training programs on AI and automation technologies
• Strong Problem-Solving skills and innovative mindset

EDUCATION

• Bachelor’s degree in information technology, computer science, business, or a related field (or equivalent experience)

PHYSICAL REQUIREMENTS:

• General Office Demands
  We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson’s pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

ESSENTIAL RESPONSIBILITIES:

The Lead Architect is responsible for designing, developing, and optimizing autonomous AI agents that possess advanced reasoning, learning, and action-taking capabilities within complex systems. This position is well-suited for individuals dedicated to advancing AI technology from passive models to proactive systems capable of planning, decision-making, adaptation, and execution in dynamic environments with minimal human intervention.
The Lead Architect will work on advanced agentic frameworks, integrate large language models with tool-use features, and contribute to multi-agent systems designed to be self-improving, goal-oriented, and robust.
Experience working in a design-centric, customer-focused environment is essential.

RESPONSIBILITIES:

• Develop and deploy modular goal-oriented agent-based AI frameworks for autonomous task execution
• Develop modular goal-oriented AI Agents that can plan, execute, and adjust multi-step analysis workflows
• Develop intuitive interfaces that facilitate interaction between AI systems and human experts
• Implement short-term and long-term memory layers, vector stores, and strategic planning pipelines to enhance agentic behavior
• Lead automation projects that utilize agentic AI to address scenarios with high levels of ambiguity, scalability, and complexity
• Lead proof-of-concept development, experimentation, optimization, and production deployment of AI agent systems
• Create reusable frameworks for AI agent tuning, evaluation, and optimization
• Conduct research and develop innovative methods in agent learning, reasoning, and human interaction
• Build and coordinate multi-agent systems that can communicate, negotiate, and collaborate to solve tasks collectively
• Create frameworks to assess agent effectiveness, safety, and alignment with human goals
• Develop and maintain comprehensive blueprints encompassing runtime, security, DevOps, and infrastructure architectures for the Agentic AI platform and related applications.
• Act as technical SME during implementation phase and ensure success by assisting in troubleshooting, reviews, problem resolution, workarounds
• Leading and participating in solution review boards for proposals, ensuring oversight of technology assurance as well as quality and risk assessments
• Establish architectural governance and perform reviews to verify adherence to practices related to security, scalability, and performance
• Evaluate and enhance AI agent performance through comprehensive data analysis and user feedback
• Adhere to AI governance to meet organizational, ethical, and policy standards