Project Role : Infrastructure Engineer
Project Role Description : Assist in defining requirements, designing and building data center technology components and testing efforts.
Must have skills : Automation Architecture
Good to have skills : NA
Minimum 7.5 Year(s) Of Experience Is Required
Educational Qualification : 15 years full time education
Summary:
As an Infrastructure Engineer, a typical day involves supporting the definition of requirements and contributing to the design and construction of data center technology components. The role includes active participation in testing activities to ensure the reliability and performance of infrastructure solutions. This position requires close collaboration with various teams to align technology implementations with organizational goals, while continuously monitoring and improving data center operations to maintain optimal functionality and efficiency.
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 7.5 years of experience in Automation Architecture.
- This position is based at our Gurugram office.
- A 15 years full time education is required.
