Director Digital Manufacturing Innovation

The Director, Digital Manufacturing Innovation (DMI), is the global business leader for digital innovation across Amgen Manufacturing. Based in Global Manufacturing Strategies and Technologies (GMST), you will identify the manufacturing opportunities where digital products, data, analytics, and AI can create the greatest value; set and manage the portfolio; and lead work from idea and pilot through supported deployment, adoption, and expansion across the network. You are accountable for ensuring that each priority has a clear product team, business owner, reliable data, an effective solution, and measurable results.

You will lead a global team and work with manufacturing sites, Digital Site Leaders, product owners, Engineering, Process Development, Quality, Supply Chain, Finance, Technology, AI and Data, and Amgen India delivery teams. DMI sets portfolio direction, business requirements, readiness expectations, and scale decisions. Product and technology teams own technical design and delivery, while sites own local implementation, adoption, and sustained performance. You will bring these groups together, resolve trade-offs, and give leaders clear recommendations on where to invest, scale, improve, or stop.

Innovation strategy and portfolio leadership

• Set and maintain the global DMI roadmap, translating Manufacturing priorities into a focused portfolio of digital, data, analytics, AI, and automation opportunities.
• Prioritize work based on patient and supply impact, safety, quality, business value, data and site readiness, risk, cost, and the potential for reuse across the network.
• Lead a consistent process from idea intake and discovery through pilot, production, and network expansion.
• Ensure every initiative has a clear problem statement, business sponsor, accountable owner, resource plan, success measures, and decision points.
• Provide clear recommendations and escalations to senior Manufacturing leaders.
• Align with Digital Site Leaders on site roadmaps, identify proven site innovations that can be reused, and evaluate emerging technologies through focused tests before broader investment.

Digital products and connected manufacturing

• Partner with product owners to define manufacturing needs, expected outcomes, roadmaps, and delivery priorities across connected operations, digital performance management, electronic workflows, workforce tools, production scheduling, and capacity planning.
• Set clear expectations for testing, release readiness, user experience, support, and lifecycle ownership.
• Ensure products are practical for operators, reliable, secure, integrated, and supported.
• Promote shared products and standards across the network while allowing local variation when a clear business need justifies it.

Manufacturing data ownership and readiness

• Establish clear business ownership and stewardship for priority Manufacturing data.
• Work with enterprise data and system owners to define common terms, master and reference data needs, data sources, and measurable data quality standards.
• Assess data readiness early and lead correction of critical gaps before digital or AI solutions advance.
• Make priority data easy to find, appropriately accessible, compatible across systems, and reusable.
• Build a network of site data champions and connect source-system stewardship to reliable data products.
• Resolve gaps in ownership, key performance indicator definitions, data quality, and integration with named owners and clear due dates.

AI and analytics in manufacturing

• Set priorities for AI, machine learning, advanced analytics, and generative AI in partnership with Manufacturing and the enterprise Technology and AI and Data team.
• Translate needs in capacity, productivity, readiness, reliability, and knowledge access into clear problem statements, requirements, baselines, and expected outcomes.
• Focus on practical applications such as daily performance management, monitoring and troubleshooting, equipment health, capacity planning and debottlenecking, knowledge access, and computer vision.
• Move successful pilots into supported production only when representative testing, data quality, human oversight, monitoring, support, and lifecycle ownership are in place.
• Work with Quality, Cybersecurity, and Technology teams to apply the right validation, data integrity, access, and change controls.
• Escalate unresolved risks before launch or expansion.

Deployment adoption and value realization

• Plan deployment waves with sites and enterprise partners based on business priority, product maturity, and local readiness.
• Confirm the people, integration work, training, and support needed before committing to a launch date, and raise unresolved ownership or resource conflicts quickly.
• Require a named site sponsor and business owner, engaged users, and a practical readiness and adoption plan before go-live.
• Partner with sites on workflow changes, training, launch support, and stabilization, with sites accountable for local implementation, adoption, and sustained results.
• Measure adoption and business impact separately from the number of deployments or users.
• Establish baselines and work with sites and Finance to confirm benefits in error and defect prevention, workforce productivity, asset performance, throughput, and capacity.
• Use the evidence to decide whether to expand, improve, or retire a solution.

People leadership and enterprise partnership

• Build, lead, and develop a global team of digital product, data, and innovation professionals.
• Set clear goals and accountability, strengthen product and data skills, and build a strong succession pipeline.
• Create trusted partnerships across Manufacturing, Engineering, Process Development, Quality, Supply Chain, Finance, Technology, AI and Data, and Amgen India.
• Resolve competing priorities, make trade-offs transparent, and communicate decisions, risks, and progress clearly to senior leaders.

How success will be measured

Success will be measured by whether the DMI portfolio is focused on the most important Manufacturing needs and whether priority capabilities move beyond pilots into reliable, supported use. Measures will include data quality and ownership, site readiness, adoption in daily work, timely portfolio decisions, reuse across the network, and sustained benefits in safety, quality, supply, productivity, asset performance, throughput, and capacity. Benefits and targets will be agreed with sites, Finance, and Manufacturing leadership.