About The Company

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

We are seeking a Lead AI Architect to define and guide enterprise-grade architecture for AI-enabled, mission-critical products and platforms. In this role, you will translate business strategy into scalable solution designs, approve end-to-end AI architectures, and help teams operationalize AI/ML capabilities securely and responsibly. You will partner across engineering, data, security, and business teams to shape target-state architecture, simplify the technology landscape, and deliver measurable outcomes in a regulated enterprise setting.

The ideal candidate will have extensive experience in designing and implementing scalable AI solutions, leading cross-functional teams, and establishing governance standards for AI/ML initiatives. This role requires a strategic thinker with a deep understanding of cloud architecture, data engineering, and enterprise security frameworks, with a focus on leveraging AI to drive business value and operational excellence.

Qualifications

Minimum requirements include a degree or equivalent with typically over 10 years of relevant experience. Candidates with advanced degrees such as a Master's or Doctorate may qualify with fewer years of experience.

Basic Requirements

- Over 10 years of experience in solution architecture, enterprise architecture, software engineering, or related technical disciplines.
- Bachelor’s degree in Computer Science, Engineering, Information Systems,



or a related field, or equivalent experience.
- Proven experience designing enterprise-scale architectures for cloud-based, distributed, and integrated systems.
- Hands-on experience with AI/ML architecture, lifecycle operationalization, and deployment patterns.
- Strong knowledge of cloud architecture, particularly with Microsoft Azure, with Azure AI Foundry experience preferred.
- Experience in defining and enforcing architecture governance, standards, and review processes.
- Excellent communication skills to articulate architecture decisions, risks, and trade-offs to both technical and non-technical stakeholders.

Preferred Skills / Experience

- Experience with enterprise architecture frameworks such as TOGAF, C4 model, or ITIL 4, along with security frameworks like OWASP Top 10.
- Experience working in multi-cloud environments, implementing CI/CD pipelines, infrastructure as code, and observability solutions.
- Background in data preparation, feature engineering, MLOps, model monitoring, and AI governance.
- Experience supporting regulated, complex, or large-scale enterprise environments.
- Proven track record leading modernization initiatives, portfolio roadmaps, or architecture integration during mergers and acquisitions.
- Ability to influence across domains and coach architectural and engineering teams effectively.

Responsibilities Design and approve comprehensive AI, data, and application architectures for enterprise platforms and high-impact initiatives, ensuring alignment with business goals and technical standards. Lead the operationalization of AI/ML lifecycles, including deployment readiness, observability,



and ongoing optimization to ensure scalable and reliable solutions.

Establish architecture standards, governance guardrails, and exception processes that support security, reliability, performance, compliance, and operational stability.

Guide cloud-native and hybrid solution strategies across cloud platforms, with a preference for Azure AI Foundry, to optimize performance and cost-efficiency.

Oversee data preparation and feature engineering approaches that enable scalable, production-ready AI solutions.

Evaluate existing platforms, integration patterns, APIs, event-driven architectures, and data flows to align current systems with future roadmaps.

Partner with product, engineering, security, and operations teams to manage technical risks, accelerate delivery timelines, and communicate trade-offs effectively to stakeholders at all levels.

Mentor and develop architects and engineers, promoting modern practices, continuous improvement, and enterprise-wide systems thinking to foster a high-performance team environment.

Benefits

McKesson offers a competitive total rewards package, including base salary, performance-based bonuses, and long-term incentives. Our compensation philosophy ensures pay is aligned with market standards and regulatory compliance. We also provide comprehensive health benefits, retirement plans, paid time off, and opportunities for professional development.

Our commitment to employee well-being extends to various wellness programs, flexible work arrangements, and a supportive work environment designed to foster growth and innovation.

Additional benefits include access to learning resources, career advancement opportunities, and participation in community engagement initiatives. We believe in investing in our employees to ensure they thrive both professionally and personally.

Equal Opportunity

McKesson is an Equal Opportunity Employer. We provide equal employment opportunities to applicants and employees without regard

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