Project Role Description : Build, configure, and test data center and AI infrastructure across compute, storage, networking, and platform layers. Translate architectural designs into scalable, secure, and high-performance production environments through reliable implementation and automation.
Must have skills : Large Language Models (LLMs)
Positive to have skills : NA
Minimum 5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary
As an Infrastructure Engineer, a typical day involves actively participating in the definition of requirements and contributing to the design and construction of data center technology components. The role includes collaborating with various teams to ensure the seamless integration and functionality of infrastructure elements. Additionally, the position requires involvement in testing activities to validate the performance and reliability of the technology components within the data center environment.
This role demands a proactive approach to problem-solving and continuous improvement to support the evolving needs of the infrastructure landscape.
Key Responsibilities
Design and build scalable agentic AI platforms supporting multi-step autonomous agents
Architect and implement Model Context Protocol (MCP) servers and client ecosystems
Develop agent adaptors for multiple LLMs, tools, and AI frameworks
Build Agent APIs (REST + gRPC) for lifecycle, streaming, and orchestration
Implement multi-agent execution patterns like ReAct and Plan-and-Execute
Enable memory, tool-calling, and context persistence for AI agents
Ensure security, observability, and reliability of agent workflows
Collaborate with ML, product, and platform teams on agentic system evolution
Required Skills And Qualifications
5+ years of software engineering with 2+ years in AI/LLM systems
Strong programming skills in Python and TypeScript / Node.js