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Manager, Agentic AI Business Solutions, Neural Nexus

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Manager, Agentic AI Business Solutions, Neural Nexus

India - Hyderabad Apply Now
JOB ID: R-240660 País: India - Hyderabad Estado: On Site DATE POSTED: Mar. 30, 2026 CATEGORÍA DE EMPLEO: Sales & Marketing Operations

In this vital role of Manager, Agentic AI Business Solutions, Neural Nexus, you will be responsible for executing and scaling Agentic AI solutions within the Neural Nexus (NN) platform, supporting Amgen’s global commercial and analytics functions. This role is focused on hands-on delivery, operationalization, and continuous enhancement of GenAI-powered capabilities, ensuring solutions are deployed efficiently, integrated seamlessly, and adopted effectively across global business teams.

You will work closely with global stakeholders across GCCI, Commercial, AI&D, and Technology teams to translate business requirements into scalable Agentic AI solutions. Operating within a global delivery model, you will coordinate across geographies to ensure consistent execution, rapid iteration, and high-quality delivery of AI capabilities that drive measurable business value.

This role is ideal for a technically strong and execution-focused person who thrives in building, deploying, and scaling AI-driven solutions in a fast-paced, globally distributed environment and has worked in a commercial organization before.

Key Responsibilities

Strategic Leadership & Roadmap Development

  • Execute against a defined Agentic AI delivery roadmap aligned to Neural Nexus priorities, focusing on scalable, reusable solutions that support global commercial use cases.

  • Break down business requirements into executable user stories, tasks, and sprint plans aligned to global priorities.

  • Support prioritization discussions by providing clear input on effort, dependencies, and delivery feasibility across workstreams.

  • Continuously identify opportunities to standardize and reuse components to accelerate execution and reduce duplication.

End-to-End Management of NN Platform Lifecycle

  • Own execution of Agentic AI solutions—from intake and design through development, testing, deployment, and post-launch support—ensuring high-quality and timely delivery.

  • Partner with AI&D and Engineering teams to enable development of GenAI agents, ensuring solutions meet defined performance, scalability, and reliability standards.

  • Drive day-to-day agile execution, including sprint planning, backlog grooming, stand-ups, and release coordination across global teams.

  • Lead hands-on coordination of UAT, defect resolution, access setup, and production deployment activities.

  • Implement monitoring and alerting mechanisms to proactively identify and resolve performance or usage issues post-deployment.

Cross-Functional Team Orchestration & Collaboration

  • Operate within a global delivery model, coordinating closely with US-based business teams, BAI, AI&D, and Technology to ensure seamless execution across time zones.

  • Serve as a key liaison between business stakeholders and technical teams, translating requirements into scalable technical solutions and ensuring alignment on scope and timelines.

  • Collaborate with data, platform, and governance teams to ensure solutions adhere to enterprise data standards, compliance requirements, and architectural guidelines.

  • Support cross-functional pods or delivery squads to accelerate development and deployment of prioritized Agentic AI capabilities.

Executive Stakeholder Management & Strategic Communication

  • Provide clear and structured updates on delivery progress, risks, and milestones to global stakeholders and program leadership.

  • Clearly communicate solution readiness, limitations, and expected outcomes to ensure alignment prior to deployment.

  • Escalate risks and delays proactively, ensuring minimal impact to committed delivery timelines.

Driving Platform Adoption & Value Realization

  • Drive immediate post-deployment adoption through hands-on support, user training, and troubleshooting for global teams.

  • Track usage, adoption, and performance metrics to ensure solutions are actively used and delivering intended value.

  • Quickly iterate on deployed solutions based on user feedback, improving usability, accuracy, and workflow integration.

  • Embed solutions directly into business workflows to eliminate manual processes and increase execution efficiency.

Change Management & Continuous Improvement

  • Execute change enablement activities as part of delivery, including user onboarding, documentation, and readiness support.

  • Capture real-time user feedback and system performance data to drive rapid iteration and enhancement cycles.

  • Standardize delivery playbooks, templates, and best practices to improve speed and consistency across deployments.

  • Continuously improve execution processes to increase delivery velocity, quality, and scalability within the global model.

Preferred Qualifications

  • Bachelor’s degree and relevant experience in AI/ML, Data Science, Analytics, Engineering, or related discipline.

  • Experience working with commercial life sciences organization.

  • Experience delivering AI/ML or Generative AI solutions in a production environment, preferably within commercial, analytics, or enterprise platforms.

  • Hands-on experience with GenAI use cases such as automation agents, LLM-powered workflows, or decision-support tools.

  • Experience working in a global delivery model, collaborating with geographically distributed teams and stakeholders.

  • Ability to translate business requirements into technical execution plans and manage delivery across cross-functional teams.

  • Strong program and delivery management skills, including agile methodologies, dependency management, and risk mitigation.

  • Communication & Interpersonal Skills: Strong ability to communicate complex technical concepts clearly to both technical and non-technical stakeholders.

  • Problem-Solving & Execution Focus: Ability to manage multiple priorities, troubleshoot delivery challenges, and drive outcomes in a matrixed organization.

  • Ethical Standards: Commitment to responsible AI use, compliance, and data integrity.

  • Experience working with global stakeholders in a regulated industry environment preferred.

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