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Amgen
Senior Digital Product Strategy and Innovation Manager (AI)
United States - Remote
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hirly's read of this role
- Seniority
- Lead / management
- Country
- US
- Work mode
- Remote-friendly
- First seen by hirly
- 8 Oct 2026
Derived automatically from the posting.
the posting
Career Category
Information Systems
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 oversight, change management, and enterprise scalability from the earliest stages of discovery.
- Lead executive and cross-functional decision forums that align business, scientific, technology, data, security, and governance stakeholders around opportunity priorities, product direction, technical tradeoffs, investment decisions, and paths to scale. Navigate competing perspectives and drive clarity and decisions in ambiguous or high-impact situations.
- Translate Amgen business and transformation priorities, emerging AI capabilities, technology strategy, and portfolio learnings into strategic product opportunity areas, identifying where reusable capabilities, platforms, data assets, or common patterns can create value across multiple functions rather than through isolated point solutions.
- Provide product leadership, coaching, and thought partnership to product managers and cross-functional teams, helping raise the maturity of AI product discovery, experimentation, evidence-based decision making, and product management practices across the organization.
- Act as a thought leader for AI product management, bringing external product, technology, and industry perspectives into Amgen and translating emerging AI capabilities into practical implications for enterprise product strategy.
What we expect of you
We are all different, yet we all use our unique contributions to serve patients. The Senior Digital Product Manager professional we seek has these qualifications.
Basic Qualifications:
Doctorate degree and 2 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
OR
Master’s degree and 6 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
OR
Bachelor’s degree and 8 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
OR
Associate’s degree and 10 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
OR
High school diploma / GED and 12 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
In addition to meeting at least one of the above requirements, you must have a minimum of 2 years of experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation of resources. Your managerial experience may run concurrently with the required technical experience referenced above.
Preferred Qualifications:
- 4+ years of product management, product strategy, innovation, consulting, digital transformation, or related experience.
- 2+ years of experience with AI, machine learning, data products, automation, LLMs, agents, NLP, analytics, or enterprise AI solutions.
- Demonstrated ability to operate effectively in high-ambiguity environments, independently frame complex problems, make sound recommendations with incomplete information, and drive alignment across stakeholders with competing priorities.
- Demonstrated experience leading AI or data products through discovery, validation, investment decision, and scale.
- Familiarity with generative AI, LLMs, retrieval-augmented generation, AI agents, prompt engineering, model orchestration, NLP, predictive analytics, or intelligent automation.
- Understanding of data architecture concepts, including data pipelines, data lakes, data warehouses, APIs, metadata, m
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