Introduction
We are seeking a Technical AI Enablement Senior Engineer who will bridge ideas to technology, partnering with infrastructure, cloud, and data teams to ensure architectural soundness, scalability, and security for AI solutions.
The role focuses on designing, building, and operationalizing AI solutions that deliver measurable business value.
This position reports directly to the VP, McKesson Technology – AI & Automation.
Key Responsibilities
Partner with infrastructure, cloud, and data teams to design and deliver scalable AI solutions.
Ensure architectural soundness, security, and compliance in all AI deployments.
Translate business ideas and requirements into technical specifications and actionable plans.
Implement best practices for code quality, testing, and deployment (MLOps, containerization, CI/CD).
Execute and support the transition of AI pilots and prototypes into fully operational, integrated solutions.
Identify and address technical challenges to ensure successful implementation and adoption.
Establish best practices for AI solution deployment and lifecycle management.
Act as a technical bridge between business, data, and technology teams.
Facilitate knowledge sharing and technical enablement across the organization.
Support the development of a robust AI capability within McKesson Technology.
Required Qualifications
5+ years of professional experience, including 2+ years in AI/automation solution deployment or technical enablement roles.
Expertise in AI and automation technologies, with hands-on experience designing and implementing solutions.
Strong architectural skills, with proven ability to ensure scalability, reliability, and security in AI systems.
Ability to translate business requirements and ideas into robust technical solutions.
Experience collaborating with infrastructure, cloud, and data teams to deliver integrated outcomes.
Excellent cross-functional communication skills.
Proven experience in developing and deploying AI solutions in production environments.
Experience implementing MLOps pipelines and containerized deployments.
Hands-on experience with AI frameworks/tools such as LangChain and OpenAI.
Experience with automation platforms (e.g., UiPath).
Knowledge of Python and SQL; ability to work with APIs.
Hands-on experience with Azure, AWS, or Google Cloud.
Familiarity with MLOps, containerization (Docker), and CI/CD pipelines for deployment.
Preferred Qualifications
Bachelor's degree or equivalent in Computer Science, Engineering, Information Technology, or related field.
Experience with cloud platforms (Azure, AWS, Google Cloud) and modern data architectures.
Hands-on experience with CI/CD, container orchestration (Kubernetes), and scalable architectures.
Certifications in AI, cloud architecture, or automation technologies.
Experience working in large, complex, multinational organizations.
Behavioral Competencies
Leadership – demonstrates technical leadership and influence.
Accountability – takes ownership for delivering robust, scalable solutions.
Adaptability – thrives in a fast-paced, evolving technology landscape.
Collaboration – works effectively with cross-functional teams.
Communication – explains complex technical concepts clearly to diverse audiences.
Problem-Solving – applies advanced engineering skills to overcome technical challenges.
Why This Role is Critical
This position is essential for turning AI pilots into operationalised, integrated solutions at scale.
By ensuring architectural soundness and partnering across teams, the Technical AI Enablement Senior Engineer enables McKesson to realise the full potential of AI and automation investments.
Compensation
Base Pay Range: €72,000 – €120,000
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