Infrastructure Engineer

Accenture; Hinoba-an; On-site; PHP 2,628,000 - 4,600,000; Full time

Job summary

Accenture in Gurugram is seeking an Infrastructure Engineer to help define requirements and design data center components, with testing and collaboration across teams to ensure reliable infrastructures.

The role demands 5+ years in software engineering and deep experience with LLM/AI systems, building agentic capabilities, security, and production-grade reliability within complex environments.

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.

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.

Skills

Python

TypeScript / Node.js

LLM / AI systems

REST / gRPC

Protocol Buffers

LangChain / LlamaIndex

Distributed systems

Cloud platforms

Security / Observability

Agent frameworks

Memory / agent memory

Guardrails / cost controls

Education

15 years full time education

Tools

REST

gRPC

Protocol Buffers

LangChain

LlamaIndex

AutoGen

Job description

Project Role

Infrastructure Engineer

Project Role Description

Assist in defining requirements, designing and building data center technology components and testing efforts.

Must Have Skills

Large Language Models (LLMs)

Good to Have Skills

NA

Experience

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
• 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. 15 years full time education

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