R-256479- Digital Product Manager (AI)

Overview

The Digital Product Manager will lead rapid validation of high-potential AI and data-driven business opportunities before major investment. The role provides strategic product leadership across business strategy, AI product innovation, data, technology, and enterprise transformation.

What you'll do

• 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.
• Identify, frame, and validate AI-enabled business opportunities across Amgen.
• Translate broad transformation themes into problem statements, hypotheses, user needs, data requirements, success metrics, and validation plans.
• Assess how LLMs, AI agents, machine learning models, NLP, automation, knowledge retrieval, analytics, and intelligent workflow tools can improve business outcomes.
• Evaluate data foundations, system integrations, architecture patterns, model capabilities, security controls, and operational support for scalable AI solutions.
• Partner with engineering, data science, and technical teams to align on scope, tradeoffs, and execution path.
• Conduct cross-industry landscape assessments to identify how AI addresses shared problem spaces and uncover macro-level trends and opportunities.
• Develop product requirements covering user experience, data availability, model performance, output quality, explainability, reliability, latency, integration, governance, and measurement.
• Synthesize validation findings into product recommendations, opportunity briefs, technical feasibility assessments, business cases, and executive-ready narratives.
• Help leaders decide where to invest, scale, or stop.
• Consider responsible AI, data privacy, model risk, cybersecurity, compliance, regulatory considerations, human oversight, change management, and enterprise scalability from discovery.
• Facilitate workshops, discovery sessions, prioritization discussions, technical feasibility reviews, user experience design, process mapping, and decision forums.
• Communicate complex AI and data concepts clearly to senior leaders and non-technical stakeholders.

What you'll need

• 8-13 years of work experience in the related field.
• Doctorate; 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 or GED and 10 years of Information Systems, Technology, Product, Digital, AI, Data, Business Transformation, or related experience.

Nice to have

• 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.
• Design thinking experience.
• Ability to evaluate AI opportunities across desirability, feasibility, viability, value, risk, scalability, and data readiness.
• Experience with AI platforms, MLOps, or enterprise AI architecture.
• Familiarity with AI and ML productization at scale.
• Strong presentation and public speaking skills with experience communicating to executives.
• Familiarity with biotech workflows, such as lab automation, computational biology, or clinical data.
• Hands-on ability to analyze product usage, model output quality, or design A/B experiments.
• Comfort working in fast-paced, cross-functional environments where priorities evolve quickly.
• Strong stakeholder management skills, including the ability to build relationships and collaborate effectively across functions and levels.
• Consulting experience, with demonstrated ability to structure and solve complex business problems.
• Experience conducting cross-industry landscape assessments to identify how AI is being leveraged to address shared problem spaces and uncover macro-level trends and opportunities.

Details

• Location: Hyderabad, India.