Amgen
Manager, Agentic AI Business Solutions, Neural Nexus
India - Hyderabad
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- Seniority
- Lead / management
- Country
- IN
- Work mode
- On-site / unstated
- First seen by hirly
- 23 Sept 2026
Derived automatically from the posting. Upload your resume above to see how the role scores against it.
the posting
Career Category
Sales & Marketing Operations
Job Description
What You Will Do
Let’s do this. Let’s change the world! In this vital role of Manager, Agentic AI Business Solutions, Neural Nexus, you will execute and scale Agentic AI solutions supporting Amgen’s global commercial and analytics functions.
You will partner with GCCI, Commercial, AI&D, and Technology teams to translate business needs into scalable AI solutions, contributing hands-on across data, prompt engineering, agent development, deployment, and adoption.
Key Responsibilities
Strategic Leadership & Roadmap Development
Execute against the Agentic AI roadmap aligned to commercial use cases.
Identify reusable agents, prompts, data assets, and solution components across use cases.
End-to-End Development of NN Platform Lifecycle
Develop Agentic AI solutions from requirements and prototyping through testing, deployment, and support.
Interpret the business case and developing mockups or AI prototypes to help validate concepts and advance initiatives.
Apply data science and prompt engineering techniques to prototype, evaluate, and optimize LLM-powered agents and workflows.
Partner with Data Scientists and AI Engineers on model selection, evaluation, prompt design, and agent performance.
Coordinate testing, UAT, releases, and post-launch performance monitoring.
Ability to work on upgrades and manage the execution of existing AI solutions.
Cross-Functional Team Orchestration & Collaboration
Coordinate across business, Data Science, Data Engineering, AI&D, Technology, and governance teams.
Translate business needs into data, model, prompt, and technical requirements.
Executive Stakeholder Management & Strategic Communication
Provide clear updates on progress, solution performance, risks, and readiness.
Communicate AI solution capabilities and limitations to business stakeholders.
Preferred Qualifications
Bachelor’s degree and relevant experience in Data Science, Data Engineering, AI/ML, Analytics, Computer Science, Engineering, or related discipline.
Advanced AI Literacy of GenAI, LLMs, and the Agentic paradigm (e.g., building and integrating intelligent agents into the broader ecosystems)
Experience developing and deploying AI/ML or Generative AI solutions, preferably within commercial life sciences.
Hands-on experience with LLMs, prompt engineering, agentic workflows, model evaluation, and AI solution prototyping.
Experience working with structured and unstructured data, data pipelines, APIs, and cloud-based data environments.
Working knowledge of Python, SQL, and modern AI/ML and data engineering tools.
Ability to translate business requirements into data, AI/ML, and technical solutions.
Strong Technical Aptitude (AI/ML): Strong conceptual and practical understanding of AI/ML technologies, with a particular emphasis on Generative AI, model development lifecycles, platform architecture, and the associated data requirements.
Communication & Interpersonal Skills: Ability to communicate technical concepts clearly across technical and business stakeholders.
Problem-Solving & Execution Focus: Ability to prototype solutions, troubleshoot technical and delivery challenges, and execute effectively in a matrixed environment.
Ethical Standards: Commitment to responsible AI use, compliance, and data integrity.
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