Establish and enhance MLOps and LLMOps practices including CI/CD, model versioning, automated testing, monitoring, and governance.
Develop scalable deployment architectures using containerization, infrastructure as code, and automation frameworks.
Partner with data scientists and product teams to transition prototypes into reliable production systems.
Implement model observability, performance monitoring, drift detection, and reliability engineering practices.
Lead technical troubleshooting, root cause analysis, and continuous improvement efforts for AI-enabled platforms.
Mentor engineers and promote engineering excellence through documentation, knowledge sharing, and best practices.
Basic Requirements
7+ years of experience designing, building, and supporting machine learning solutions in enterprise environments.
Bachelor's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience.
Strong software engineering experience with Python and modern application development practices.
Experience deploying machine learning models into production cloud environments.
Hands-on experience with MLOps including CI/CD pipelines, model lifecycle management, automation, and monitoring.
Experience with Azure Machine Learning, Azure Databricks, or comparable cloud-based machine learning platforms.
Experience with containerization technologies such as Docker and production deployment patterns.
Ability to communicate technical concepts effectively to both technical and business stakeholders.
Preferred Skills/Experience
Experience developing and deploying Generative AI and Large Language Model (LLM) solutions.
Experience with Azure AI Foundry, prompt engineering, evaluation frameworks, and AI guardrails.
Knowledge of LLMOps practices, RAG architectures, model evaluation, and AI observability.
Experience with Terraform or other Infrastructure-as-Code tools.
Experience with Kubernetes, AKS, distributed computing, or large-scale data processing platforms.
Familiarity with AI governance, responsible AI, security, privacy, and compliance practices.
Experience in healthcare, supply chain, pharmaceutical, or distribution industries.
Prior experience mentoring engineers and leading complex, cross-functional initiatives.
Travel / Work Environment / Physical Requirements
Travel may be required based on business needs.
Position may be remote, hybrid, or office-based depending on organizational requirements.
Must be able to perform standard computer-based work activities and communicate effectively with internal and external stakeholders.
At McKesson, we care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse employee population and ensure they are the healthiest versions of themselves.
As part of Total Rewards, we are proud to offer a competitive compensation package at McKesson. 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.
Our Base Pay Range for this position
€72,000 - €120,000
McKesson has become aware of online recruiting-related scams in which individuals who are not affiliated with or authorized by McKesson are using McKesson’s (or affiliated entities, like CoverMyMeds or RxCrossroads) name in fraudulent emails, job postings or social media messages. In light of these scams, please bear the following in mind:
McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
McKesson Talent Advisors do not communicate with candidates via online chatrooms or using email accounts such as Gmail or Hotmail. Note that McKesson does rely on a virtual assistant (Gia) for certain recruiting-related communications with candidates.
McKesson job postings are posted on our career site: careers.mckesson.com.
