Manager, Agentic AI Business Solutions, Neural Nexus

Amgen Technology; Hyderabad; Vor Ort; INR 2.800.000 - 4.500.000; Vollzeit

Zusammenfassung

Amgen Technology seeks a Manager, Agentic AI Business Solutions to design, build, and scale Agentic AI solutions across Amgen’s global commercial and analytics functions. You will lead end-to-end lifecycle work—from requirements through deployment and adoption—and partner with data science, data engineering, AID, and technology teams to translate business needs into scalable AI solutions.

With strong GenAI literacy and hands-on experience in LLMs, you will develop prototypes, evaluate models,

Qualifikationen

• Bachelor's degree in data science, AI/ML, engineering, or related field.
• Hands-on experience with GenAI, LLMs, and AI/ML solution deployment.
• Experience building AI/agentic workflows and evaluating models.

Aufgaben

• Translate business needs into scalable Agentic AI solutions.
• Develop and deploy AI/ML prototypes through prototyping, testing, and deployment.
• Coordinate testing, UAT, releases, and post-launch monitoring.
• Lead cross-functional collaboration across business, data science, data engineering, AID, and governance teams.
• Communicate solution capabilities and risks to stakeholders.

Kenntnisse

GenAI

LLMs

Prompt engineering

AI/ML

Data pipelines

Python

SQL

Cloud platforms

Communication

Ausbildung

Bachelor's degree in a relevant field

Tools

Python

SQL

Cloud platforms

Jobbeschreibung

What You Will Do

Lets do this. Lets change the world! In this vital role of Manager, Agentic AI Business Solutions, Neural Nexus, you will execute and scale Agentic AI solutions supporting Amgens global commercial and analytics functions.

You will partner with GCCI, Commercial, AID, 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, AID, 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

Bachelors 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.