Infrastructure Engineer

Project Role : Infrastructure Engineer

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)

Good 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

Hands-on experience building production LLM or agentic systems

Solid understanding of LLM fundamentals (tokens, context, tools, prompts)

Experience with API design (REST, gRPC, Protocol Buffers)

Familiarity with agent frameworks (LangChain, LlamaIndex, AutoGen, etc.)

Experience with distributed systems and cloud platforms

Degree in Computer Science or equivalent practical experience

Must To Have Skills

Deep experience with agentic AI systems and autonomous workflows

Strong knowledge of Model Context Protocol (MCP) or similar standards

Expertise in LLM tool-calling, function execution, and orchestration

Experience implementing multi-step reasoning agents

Practical knowledge of vector databases and agent memory

Ability to design guardrails, safety checks, and cost controls for AI agents

Experience with real-time streaming and multi-turn agent interactions

Proven ability to move AI research concepts into production platforms

Additional Information

• The candidate should have minimum 5 years of experience in Large Language Models (LLMs).
• This position is based at our Gurugram office.
• A 15 years full time education is required.