Digital Product Manager (AI)

Amgen·India·Onsite

Senior Product ManagerAIHealthcare

Experience

4+ years

Employment

Full Time

Work mode

Onsite

Level

Senior Product Manager

Location

India

Posted

4 days ago

What you'll do

Hyderabad
JOB ID: R-256477 LOCATION: India
Hyderabad WORK LOCATION TYPE: On Site DATE POSTED: Sep. 30, 2026 CATEGORY: Strategy and Innovation
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. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. 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.
We are seeking a Digital Product Manager, to join the AI & Data Innovation Lab Product Management Team. This role is focused on rapidly validating high-potential AI and data-driven business opportunities before major investment, helping Amgen determine which AI initiatives should be scaled, refined, paused, or redirected.
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.
This role requires a strong product mindset, sufficient technical depth to evaluate whether AI and data opportunities are practical, scalable, measurable, and aligned to Amgen’s enterprise technology direction. The successful candidate will understand how AI products are built, validated, deployed, monitored, and scaled in complex enterprise environments.
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 clear problem statements, testable hypotheses, user needs, data requirements, success metrics, and validation plans.

What you'll bring

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.
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.