Role at a glance
- Job function
-
AI & Data Large Language Model (LLM) Engineering
- Salary
- Not Disclosed
- Location
- Gurugram
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- Minimum 7.5 year(s) of experience is required
- Education
- 15 years full time education
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Role Summary
The Infrastructure Engineer builds scalable agentic AI platforms and data center technology components across infrastructure and platform layers. The role collaborates with ML, product, and platform teams to integrate, test, secure, observe, and evolve reliable AI agent systems.
What You'll Do
- 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 using REST and gRPC for lifecycle, streaming, and orchestration
- Implement multi-agent execution patterns like ReAct and Plan-and-Execute
- Ensure security, observability, and reliability of agent workflows
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Large Language Models (LLMs); 5+ years of software engineering with 2+ years in AI/LLM systems; Python and TypeScript / Node.js; production LLM or agentic systems; REST, gRPC, Protocol Buffers; distributed systems and cloud platforms; Degree in Computer Science or equivalent practical experience; agentic AI systems and autonomous workflows; Model Context Protocol (MCP); LLM tool-calling, function execution, and orchestration; multi-step reasoning agents; vector databases and agent memory; guardrails, safety checks, and cost controls; real-time streaming and multi-turn agent interactions
Required
- Large Language Models (LLMs)
- 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
Original job description
Content provided by the employer
Original job description
Content provided by the employer
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
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
About the company
Accenture
Large Enterprise
Accenture is a global professional services company that specializes in providing consulting, technology, and outsourcing services. With a diverse range of industries served, including financial services, healthcare, and telecommunications, Accenture leverages advanced technologies and data analytics to help organizations improve their performance and drive innovation. Committed to sustainable progress, the company emphasizes its dedication to inclusivity, digital transformation, and building a more sustainable future for its clients and communities. With a presence in over 120 countries, Accenture is known for its expertise in integrating cutting-edge solutions that address complex business challenges.