Digital Product Manager, Strategy and Innovation

This is a fully remote position, open to applicants in United States.

📋 Description

• Identify, frame, and validate business opportunities enabled by AI throughout Amgen.

• Convert broad transformation themes into precise problem statements, testable hypotheses, user needs, data requirements, success metrics, and validation plans.

• Assess whether proposed AI initiatives have the necessary data foundations, system integrations, architectural patterns, model capabilities, security controls, and operational support to transition 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, comprehend technical trade-offs, and identify dependencies early in the validation process.

• Design and implement rapid discovery sprints, prototypes, pilots, user research, and experiments to evaluate desirability, feasibility, viability, value, and risk.

• Utilize evidence to decide whether opportunities should advance, pivot, pause, or scale.

• Evaluate how LLMs, AI agents, machine learning models, NLP, automation, knowledge retrieval, analytics, and intelligent workflow tools can enhance productivity, decision quality, scientific discovery, operational efficiency, and workforce effectiveness.

• Develop product requirements that consider user experience, data availability, model performance, output quality, explainability, reliability, latency, integration needs, governance, and ongoing measurement.

• Synthesize findings from validation efforts into clear product recommendations, opportunity briefs, technical feasibility assessments, business cases, and executive-ready narratives.

• Assist leaders in making informed decisions regarding investments, scaling, or discontinuation.

• Maintain a portfolio of AI opportunity experiments at various stages: discovery, prototype, pilot, and scale-readiness.

• Monitor progress, risks, assumptions, evidence, data dependencies, architecture implications, and decision points.

• Ensure validation activities account for responsible AI, data privacy, model risk, cybersecurity, compliance, regulatory considerations, human oversight, change management, and enterprise scalability from the early discovery phases.

• Facilitate workshops, discovery sessions, prioritization discussions, technical feasibility reviews, user experience design, process mapping, and decision forums.

• Clearly communicate complex AI and data concepts in a business-oriented manner for senior leaders and non-technical stakeholders.

⛳️ Requirements

• Doctorate; or

• Master’s degree with 2 years of experience in Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or a related field; or

• Bachelor’s degree with 4 years of experience in Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or a related field; or

• Associate’s degree with 8 years of experience in Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or a related field; or

• High School Diploma or GED with 10 years of experience in Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or a related field.

• Over 4 years of experience in product management, product strategy, innovation, consulting, digital transformation, or a related field.

• More than 2 years of experience with AI, machine learning, data products, automation, LLMs, agents, NLP, analytics, or enterprise AI solutions.

• Proficient understanding 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.

• Knowledge of data architecture concepts, including data pipelines, data lakes, data warehouses, APIs, metadata, master data, data governance, and data quality.

• Acquainted with enterprise AI platforms, MLOps, model lifecycle management, responsible AI practices, and AI governance.

• Capability to collaborate with technical teams to assess solution architecture, integration complexity, platform suitability, security implications, and operational scalability.

• Experience in executing product discovery, design thinking, lean startup, rapid prototyping, experimentation, pilots, or proof-of-concept initiatives.

• Ability to evaluate AI opportunities based on desirability, feasibility, viability, value, risk, scalability, and data readiness.

• Background in 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 in conveying technical recommendations to senior leaders.

• Hands-on experience in analyzing user feedback, usage data, workflow metrics, model outputs, experiment results, or AI product performance.

• Comfort in fast-paced, cross-functional environments where priorities can change rapidly.

🏝️ Benefits

• A comprehensive employee benefits package, which includes 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; for field sales representatives, a sales-based incentive plan.

• Stock-based long-term incentives.

• Award-winning time-off plans.

• Flexible work models where feasible.