Salary
💰 $159,488 - $199,318 per year
About the role
- 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.
Lead the strategy, and execution of AI products and platforms across Amgen
Build and deliver intelligent tools that accelerate scientific discovery, streamline R&D workflows, and enable smarter decision-making
Operate autonomously and cross-functionally—partnering with engineering, data scientists, software engineers and domain experts
Translate the potential of LLMs, agent-based AI, and ML platforms into high-impact solutions for scientific users
Act as the Product Owner within an Agile framework
Serve as a key liaison between cross-functional teams, including Business, and external partners
Oversee the end-to-end lifecycle of AI and machine learning initiatives from inception thru scale
Own the scaling process for AI products, implementing standard methodologies in product and platform scaling to ensure AI solutions are enterprise-ready
Own product metrics, usage analytics, and model performance KPIs; iterate based on data and feedback
Engage directly with scientists, researchers, and internal stakeholders to deeply understand problems and validate solutions
Requirements
- Doctorate degree and 2 years of Information/Tech Systems experience
Or Master’s degree and 4 years of Information/Tech Systems experience
Or Bachelor’s degree and 6 years of Information/Tech Systems experience
Or Associate’s degree and 10 years of Information/Tech Systems experience
Or High school diploma / GED and 12 years of Information/Tech Systems experience
Preferred: 8+ years of product management (or related) experience; 5+ years in AI/ML or data-driven enterprise products
Experience with AI platforms, MLOps, or enterprise AI architecture
Deep familiarity with AI (e.g., LLMs, agents, NLP) and ML productization at scale
Strong presentation and public speaking skills with experience communicating to executives
Familiarity with biotech workflows (e.g., lab automation, computational biology, clinical data, etc)
Hands-on ability to analyze product usage, model output quality, or build A/B experiments