Infrastructure Engineer

About the Role

We are seeking an experienced Infrastructure Engineer to join our dynamic team at Accenture in Gurugram, Haryana. In this role, you will play a crucial part in the definition, design, and construction of advanced data center technology components, with a strong emphasis on Large Language Models (LLMs) and agentic AI platforms.

Key Responsibilities

• Contribute to defining requirements and designing scalable agentic AI platforms that support multi-step autonomous agents.
• Architect and implement Model Context Protocol (MCP) servers and their client ecosystems.
• Develop adaptable agent components for various LLMs, tools, and AI frameworks.
• Build robust Agent APIs (REST and gRPC) for managing agent lifecycles, streaming data, and orchestration.
• Implement and refine multi-agent execution patterns, such as ReAct and Plan-and-Execute.
• Integrate capabilities for memory, tool-calling, and context persistence for AI agents.
• Ensure the security, observability, and reliability of AI agent workflows.
• Collaborate closely with Machine Learning, product, and platform teams to drive the evolution of agentic systems.

Required Skills and Qualifications

• Minimum of 7.5 years of experience, with a significant focus on Large Language Models (LLMs).
• 5+ years of software engineering experience, including at least 2 years in AI/LLM systems.
• Proficiency in programming languages such as Python and TypeScript / Node.js.
• Hands-on experience in building and deploying production LLM or agentic systems.
• Solid understanding of fundamental LLM concepts, including tokens, context windows, tool usage, and prompt engineering.
• Experience with API design principles, including REST, gRPC, and Protocol Buffers.
• Familiarity with leading agent frameworks like LangChain, LlamaIndex, and AutoGen.
• Experience with distributed systems and cloud computing platforms.
• A degree in Computer Science or equivalent practical experience is required.
• 15 years of full-time education is a mandatory requirement.

Must-Have Expertise

• Deep experience with agentic AI systems and autonomous workflow development.
• Strong knowledge of Model Context Protocol (MCP) or analogous industry standards.
• Expertise in LLM capabilities such as tool-calling, function execution, and orchestration.
• Proven ability to implement multi-step reasoning agents.
• Practical knowledge of vector databases and agent memory management.
• Ability to design and implement guardrails, safety checks, and cost control mechanisms for AI agents.
• Experience with real-time data streaming and managing multi-turn agent interactions.
• Demonstrated ability to translate AI research concepts into functional production platforms.