Senior Digital Product Strategy and Innovation Manager (AI)

Career Category

Information Systems

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Job Description

Join Amgen’s Mission of Serving Patients

At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do.

Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. Amgen is advancing a broad and deep pipeline and portfolio of medicines to treat heart disease, obesity and obesity-related conditions, rare diseases, inflammatory conditions and cancer.  As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives.

Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career.

Senior Digital Product Strategy and Innovation Manager (AI)

What you will do

Let’s do this. Let’s change the world. We are seeking a Senior Digital Product Manager, to join the AI & Data Lab Product Management Team. This role will lead the identification, evaluation, and validation of high-potential AI and data-driven opportunities across Amgen, shaping strategic opportunities and providing evidence-based recommendations that inform enterprise investment and scaling decisions.

The Senior Digital Product Manager will establish product discovery and validation approaches that enable Amgen to determine where AI can create meaningful business and patient value, where opportunities warrant further investment, and where initiatives should be redirected, paused, or stopped.

Operating at the intersection of business strategy, AI product innovation, data, technology, and enterprise transformation, this role will provide strategic product leadership across ambiguous, cross-functional opportunities and influence senior business and technology stakeholders on product direction, prioritization, investment, and scale.

Responsibilities:

• Lead the identification, framing, prioritization, and validation of a variety of AI-enabled business opportunities across Amgen, ensuring resources and validation efforts are focused on opportunities with the greatest potential enterprise value and strategic alignment.
• Evaluate whether proposed AI opportunities have the right data foundations, system integrations, architecture patterns, model capabilities, security controls, and operational support needed to move from concept to scalable solution.
• Collaborate with data scientists, ML engineers, data engineers, software engineers, solution architects, platform teams, and cybersecurity partners to shape solution concepts, understand technical tradeoffs, and identify dependencies early in the validation process.
• Design and execute rapid discovery sprints, prototypes, pilots, user research, and experiments to assess desirability, feasibility, viability, value, and risk. Use evidence to determine whether opportunities should advance, pivot, pause, or scale.
• Assess how LLMs, AI agents, machine learning models, NLP, automation, knowledge retrieval, analytics, and intelligent workflow tools can improve productivity, decision quality, scientific discovery, operational efficiency, and workforce effectiveness.
• Develop product requirements that account for user experience, data availability, model performance, output quality, explainability, reliability, latency, integration needs, governance, and ongoing measurement.
• Synthesize findings from validation work into clear product recommendations, opportunity briefs, technical feasibility assessments, business cases, and executive-ready narratives.
• Provide senior leaders with clear, evidence-based recommendations on investment, prioritization, scaling, and termination decisions, including explicit articulation of tradeoffs, uncertainties, dependencies, and risks.
• Own and actively manage a portfolio of AI opportunities across discovery, prototype, pilot, and scale-readiness stages, balancing strategic value, feasibility, risk, resource requirements, dependencies, and organizational readiness.
• Ensure validation efforts consider responsible AI, data privacy, model risk, cybersecurity, compliance, regulatory considerations, human overs…