ADP _ Hiring Agentic AI Role

Work Mode - Hybrid

Hybrid Model

Role: Compute - Infrastructure Automation

Experience: 4 to 5 Years

Role Summary

We are seeking a highly motivated AI Engineer with 4-5 years of hands-on experience in designing and implementing Agentic AI solutions for enterprise infrastructure operations. The ideal candidate will have experience building MCP (Model Context Protocol)-based AI agents, integrating Large Language Models (LLMs) with infrastructure platforms, and developing autonomous workflows to streamline day-to-day infrastructure operations, This role will focus on creating AI-driven solutions across VMware, cloud platforms, containers, operating systems enabling intelligent automation and enhanced operational efficiency.

Key Responsibilities

• Design, develop, and deploy Agentic AI frameworks for infrastructure operations and engineering use cases.
• Build and integrate MCP-compliant AI agents capable of interacting with infrastructure tools and enterprise systems.
• Develop LLM-powered assistants
• Design and implement Retrieval-Augmented Generation (RAG) architectures using enterprise knowledge repositories.
• Integrate AI agents with infrastructure platforms (Virtualization, Containers, Cloud platforms)
• Implement human-in-the-loop approval workflows for critical infrastructure operations.
• Create observability mechanisms to monitor agent performance, decision quality, and execution outcomes.
• Collaborate with infrastructure, platform engineering, and security teams to establish governance for AI-driven automation.

Required Qualifications

• 4 - 5 years of hands-on AI engineering roles.
• Proven experience building Agentic AI applications
• Proficiency in Python programming.
• Experience with REST APIs, JSON, and integration development.
• Experience using Git-based development workflows and CI/CD pipelines.

Desired Skills

• Ability to translate infrastructure challenges into AI-driven solutions.
• Excellent communication and stakeholder management skills.
• Passion for innovation and continuous learning in the AI domain.