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Accenture

Advises businesses and runs their technology

Infrastructure Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeGurugram, Haryana, IndiaNo salary listed

About the Job

Requirements

  • A minimum of 7.5 years of experience in Automation Architecture is required.
  • At least 5 years of software engineering experience and 2 years in AI/LLM systems are required.
  • Strong programming skills in Python and TypeScript or Node.js are required.
  • Hands-on experience building production LLM or agentic systems is required.
  • A solid understanding of LLM fundamentals, including tokens, context, tools, and prompts, is required.
  • Experience with API design using REST, gRPC, and Protocol Buffers is required.
  • Familiarity with agent frameworks such as LangChain, LlamaIndex, or AutoGen is required.
  • Experience with distributed systems and cloud platforms is required.
  • A degree in Computer Science or equivalent practical experience is required.
  • Deep experience with agentic AI systems and autonomous workflows is required.
  • Strong knowledge of Model Context Protocol (MCP) or similar standards is required.
  • Expertise in LLM tool-calling, function execution, and orchestration is required.
  • Experience implementing multi-step reasoning agents is required.
  • Practical knowledge of vector databases and agent memory is required.
  • Ability to design guardrails, safety checks, and cost controls for AI agents is required.
  • Experience with real-time streaming and multi-turn agent interactions is required.
  • Proven ability to move AI research concepts into production platforms is required.
  • Fifteen years of full-time education is required.

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 large language models (LLMs), tools, and AI frameworks.
  • Build Agent APIs using REST and gRPC for lifecycle management, streaming, and orchestration.
  • Implement multi-agent execution patterns such as 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 machine learning, product, and platform teams on agentic system evolution.
  • Support the definition of requirements and contribute to the design and construction of data center technology components.
  • Participate in testing to ensure infrastructure solution reliability and performance.
  • Monitor and improve data center operations to maintain functionality and efficiency.
  • 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.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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