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 7.5 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 7.5 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 Important Notice We have been alerted to the existence of fraudulent messages asking job seekers to set up payment to cover various costs associated with establishing employment at Accenture. No one is ever required to pay for employment at Accenture. If you are contacted by someone asking for payment, please do not respond, and contact us at india.fc.check@accenture.com immediately. Equal Employment Opportunity Statement All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.