AI Platform & Digital Product Manager– Neural Nexus

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Amgen

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Nexus Modular Analytics

Job Description

What You Will Do

Let’s do this. Let’s change the world!

Neural Nexus (NN) is Amgen’s enterprise AI initiative that powers the development and scaling of generative and agentic AI solutions across Commercial, Medical, and analytics functions.

In this vital role of AI Platform & Product Manager – Neural Nexus, you will be responsible for executing and scaling key components of the Neural Nexus (NN) platform roadmap, supporting Amgen’s enterprise AI platform across Commercial, Medical, and AI&D functions.

This role is focused on translating defined platform priorities into scalable, user-centric, and production-ready solutions, ensuring capabilities are designed, built, and integrated effectively within the broader platform. You will lead delivery of both high-impact experiences (e.g., executive cockpit/command center) and platform capabilities (e.g., integrations, reusable services, and new persona solutions such as Analytics and Execution workspaces).

Operating within a global delivery model, you will partner closely with Neural Nexus peers, Technology, AI&D, and business teams to ensure consistent execution, rapid iteration, and measurable business value.

Key Responsibilities

Platform Execution & Delivery

  • Execute against the Neural Nexus platform roadmap, translating priorities into scalable, high-quality platform capabilities
  • Own end-to-end delivery from design through deployment and iterative enhancement
  • Determine how solutions are structured, built, and scaled within defined platform guardrails

Experience Development & Scaling

  • Lead development of key platform experiences (e.g., AI-powered Executive Command Center, Analytics Workspaces) with a focus on usability, performance, and adoption
  • Drive solutions from POC to production, ensuring scalability, reuse, and alignment with platform standards
  • Leverage GenAI/LLM-powered capabilities and agent-based workflows to deliver intelligent solutions
  • Continuously refine capabilities based on user feedback and usage insights

Platform Integration & Reuse

  • Drive integration with enterprise data systems, AI/ML models, and external tools
  • Partner with Technology and AI&D to align with architecture, data, and GenAI standards
  • Promote modular, reusable components to accelerate scaling and reduce duplication

Cross-Functional Execution

  • Translate business needs into clear execution plans, aligning stakeholders on scope, timelines, and outcomes
  • Coordinate across global teams to ensure consistent delivery across a distributed model
  • Identify and resolve risks, dependencies, and bottlenecks

Adoption & Value Realization

  • Ensure solutions are embedded into business workflows and drive measurable impact
  • Track adoption, usage, and performance metrics to optimize delivery outcomes
  • Partner with change management and training teams to support adoption

Continuous Improvement

  • Iterate on platform capabilities based on feedback and performance data
  • Contribute to platform playbooks, standards, and best practices
  • Identify opportunities to enhance capabilities through improved design or new AI approaches

Preferred Qualifications

  • Bachelor’s degree in AI/ML, Data Science, Computer Science, Analytics, Engineering, or related discipline.
  • Minimum 5 years of experience in Pharma/Biotech commercial operations, analytics and reporting experience
  • 2–3 years of experience in analytics, data, AI/ML, or technology delivery roles.
  • 5-8 years of experience in digital platform product management, AI/ML-driven solutions, or enterprise digital product development
  • Proven experience executing and scaling platform or product initiatives, delivering production-ready solutions
  • Experience delivering across:
  • 0→1 (POCs, rapid prototyping)
  • 1→N (scaling, enterprise rollout)
  • Strong understanding of Generative AI / LLM-based applications, including agentic workflows
  • Experience working with engineering and data science teams to deliver AI-powered solutions
  • Experience driving system integration and platform interoperability
  • Strong product mindset with focus on usability, reuse, and business impact
  • Ability to translate business requirements into execution plans and drive delivery across cross-functional teams
  • Experience operating in a global delivery model
  • Strong execution, problem-solving, and stakeholder management skills
  • Excellent communication skills across technical and business audiences

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