Manager, Agentic AI Business Solutions, Neural Nexus

Amgen · Hyderabad

  • Experience3–4 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Posted25 Sept 2026

About Amgen

Amgen is hiring in Hyderabad in pharma biotech. This role looks for around 3+ years of experience.

Skills

  • Generative AI
  • LLMs
  • prompt engineering
  • agentic workflows
  • model evaluation
  • AI solution prototyping
  • Python
  • SQL
  • data pipelines
  • APIs
  • cloud-based data environments
  • AI/ML
  • data science
  • data engineering

The role

A Generative AI Engineer at a biopharmaceutical company develops agentic AI solutions for commercial analytics using Generative AI, prompt engineering, and agentic workflows, while applying model evaluation and AI solution prototyping.

Full 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.