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Lead Agentic AI Solutions Architect

Job in Mississauga, Ontario, Canada
Listing for: McKesson
Part Time position
Listed on 2026-09-03
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, Cloud Engineer - Software, DevOps
Salary/Wage Range or Industry Benchmark: 169000 - 226000 CAD Yearly CAD 169000.00 226000.00 YEAR
Job Description & How to Apply Below

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.

About the Role

McKesson is seeking an experienced Lead Agentic AI Solutions Architect to lead the end-to-end delivery of enterprise AI and automation solutions that transform business operations and improve healthcare outcomes. This role owns the full lifecycle of Agentic AI and automation solution delivery, from strategy and architecture through implementation, deployment, and optimization.

You will partner closely with business, product, engineering, and enterprise architecture teams to identify high-value opportunities, design scalable AI solutions, and ensure responsible AI practices are embedded throughout the development lifecycle. This role is ideal for a technology leader passionate about building enterprise-grade agentic systems powered by large language models, modern AI frameworks, and cloud-native platforms.

What You'll Do
  • Own the full lifecycle of Agentic AI and automation solutions, from discovery and architecture through deployment and operational support.
  • Identify, prioritize, and deliver high-impact AI use cases aligned with business strategies and measurable outcomes.
  • Design scalable Agentic AI architectures integrated with Agent Hub, enterprise platforms, APIs, and business workflows.
  • Lead technical design decisions involving LLMs, AI agents, retrieval systems, orchestration frameworks, and automation technologies.
  • Partner with business and technology stakeholders to define requirements, solution roadmaps, and implementation strategies.
  • Establish engineering standards, architecture patterns, governance controls, and reusable AI capabilities.
  • Drive Responsible AI practices including governance, security, observability, risk management, and human oversight.
  • Mentor engineers and architects while promoting technical excellence, innovation, and continuous improvement.
Minimum Requirements

-Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master'sor Doctorate qualifications

PHYSICAL REQUIREMENT:

General Office Demands, We are Flex and Connect with 2 days a week in office

Critical Skills -
  • 10+ years of software engineering, solution architecture, application development, or platform engineering experience.
  • 5+ years of experience designing and implementing AI-enabled enterprise solutions.
  • Hands-on experience building AI, machine learning, automation, or intelligent workflow solutions in enterprise environments.
  • Strong proficiency in Python and Agentic software engineering practices.
  • Experience designing enterprise integrations using MCPs, APIs, microservices, and event-driven architectures.
  • Proven experience leading technical delivery across multiple teams and stakeholders.
  • Excellent communication, collaboration, and solution leadership skills.
Preferred Skills
  • Strong understanding of Large Language Models (LLMs), tokenization, context windows, and model capabilities.
  • Experience with Lang Chain, Lang Graph, Semantic Kernel, Auto Gen, Claude Agent SDK, or similar frameworks.
  • Experience designing function-calling patterns, tool integrations, and structured schemas.
  • Expertise with Azure Cloud services, Azure AI Foundry, and cloud-native architecture patterns.
  • Experience with Docker, Kubernetes, CI/CD pipelines, and modern deployment practices.
  • Experience implementing Human-in-the-Loop processes for critical business workflows.
  • Understanding of Responsible AI principles, governance frameworks, risk management, and compliance requirements.
Travel / Work Environment /

Physical Requirements
  • Position may require limited travel (up to 10%) for business…
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