Digital Product Manager, Strategy and Innovation

Role Overview

• Identify, frame, and validate AI-enabled business opportunities across Amgen.
• Translate broad transformation themes into clear problem statements, testable hypotheses, user needs, data requirements, success metrics, and validation plans.
• 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.
• Help leaders make informed decisions about where to invest, scale, or stop.
• Maintain a portfolio of AI opportunity experiments across stages of discovery, prototype, pilot, and scale-readiness.
• Track progress, risks, assumptions, evidence, data dependencies, architecture implications, and decision points.
• 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.
• Facilitate workshops, discovery sessions, prioritization discussions, technical feasibility reviews, user experience design, process mapping, and decision forums.
• Communicate complex AI and data concepts in a clear, business-oriented way for senior leaders and non-technical stakeholders.

Requirements

• Doctorate degree OR Master’s degree and 2 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience OR Bachelor’s degree and 4 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience OR Associate’s degree and 8 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience OR High school diploma / GED and 10 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience
• 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.
• Working knowledge of AI product development, including discovery, prototyping, model evaluation, deployment, monitoring, and iteration.
• 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, master data, data governance, and data quality.
• Familiarity with enterprise AI platforms, MLOps, model lifecycle management, responsible AI practices, and AI governance.
• Ability to partner with technical teams to assess solution architecture, integration complexity, platform fit, security implications, and operational scalability.
• Experience running product discovery, design thinking, lean startup, rapid prototyping, experimentation, pilots, or proof-of-concept initiatives.
• Ability to evaluate AI opportunities across desirability, feasibility, viability, value, risk, scalability, and data readiness.
• Experience developing business cases, opportunity assessments, technical feasibility summaries, executive narratives, or investment recommendations.
• Familiarity with biotech, pharmaceutical, R&D, manufacturing, medical, or enterprise business workflows.
• Strong presentation and storytelling skills, including experience communicating technical recommendations to senior leaders.
• Hands-on ability to analyze user feedback, usage data, workflow metrics, model outputs, experiment results, or AI product performance.
• Comfort working in fast-paced, cross-functional environments where priorities evolve quickly.

Tech Stack

• Cyber Security

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
• group medical, dental and vision coverage
• life and disability insurance
• flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models where possible.