Program Manager, Manufacturing & Supply AI Transformation

The Program Manager for Manufacturing & Supply AI Transformation will lead the execution of Opella’s data and AI initiatives, translating strategic goals into actionable, value-generating solutions across the global manufacturing and supply chain network. This role sits at the heart of the MS.AI Factory, coordinating cross-regional initiatives and embedding AI-enabled capabilities into operational processes.

Key Responsibilities:

• Program Execution: Manage end-to-end delivery of AI initiatives, from use-case intake and feasibility assessment to deployment and adoption.
• Operational Leadership: Partner with Manufacturing, Supply, IT, Data Science, Quality, and Finance teams to ensure operational readiness and disciplined governance.
• Innovation: Advocate for modern digital solutions, including AI agents and automation, while fostering a culture of experimentation.
• Stakeholder Engagement: Lead change management efforts, including Copilot enablement and the AI Champions network, across Europe and India.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related quantitative discipline; advanced degree preferred.
• 8+ years of experience managing large-scale transformation or digital programs.
• Strong hands-on development skills in Python and production-ready software engineering practices (OOP, CI/CD, testing).
• Experience designing and deploying LLM-powered and agentic solutions (RAG, multi-agent systems, prompt engineering).
• Proven ability to integrate solutions into enterprise systems (MES, QMS, ERP/SAP).
• Experience operationalizing models and agents using MLOps/AgentOps tools (MLflow, Kubeflow, Azure DevOps).
• Familiarity with cloud platforms (Azure, AWS, GCP) and data tools (Databricks, Snowflake, Spark).
• Strong understanding of AI/ML lifecycles and business translation of technical requirements.

Preferred Qualifications

• Experience in life-sciences or regulated (GxP) manufacturing environments.
• Demonstrated success in deploying data, analytics, and automation at scale.