Lead LLM / Agentic AI Engineer – AI-Led Procurement Transformation

Location: Kolkata

Experience: 8+ Years

Budget: Up to ₹3 Lakh/month

Work Mode: Onsite / Client-facing

Travel: May be required

Cloud: AWS preferred / important

About the Role

We are looking for an experienced Lead LLM / Agentic AI Engineer to lead an AI-led transformation initiative for the Procurement function.

The candidate will design and develop a Procurement Category Insights Engine combining Classical Machine Learning, Statistical Modelling, LLMs, Generative AI and Agentic AI.

This is not a basic chatbot or RAG development role. The ideal candidate should have hands-on experience building production-grade Multi-Agent AI solutions, integrating real-time and external data sources, APIs, ERP/enterprise systems, and deploying scalable AI applications.

The role requires someone who can take a business problem from

Business Problem → AI Architecture → Multi-Agent Solution → Enterprise Integration → Production Deployment → Client Handover

Key Responsibilities

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Lead architecture and development of enterprise-grade LLM, GenAI and Agentic AI solutions.

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Design and implement Multi-Agent AI workflows capable of reasoning, planning and executing multi-step tasks.

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Build and orchestrate specialized AI agents for procurement-related use cases.

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Design agent workflows, state management, tool calling and API integrations.

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Develop the Procurement Category Insights Engine using ML, statistical modelling and GenAI.

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Integrate internal, external and real-time data sources.

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Integrate AI solutions with ERP and enterprise applications.

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Build tools/API layers that enable agents to retrieve information and perform approved business actions.

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Develop RAG-based solutions for enterprise knowledge and contextual understanding.

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Implement prompt engineering, agent instructions, guardrails and evaluation mechanisms.

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Implement LLM monitoring, evaluation and performance optimization.

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Integrate classical ML/statistical models with GenAI applications.

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Work closely with Data Scientists, Backend Engineers and Frontend Engineers to deliver end-to-end solutions.

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Ensure solutions are scalable, secure, reliable and production-ready.

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Lead technical discussions with client stakeholders.

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Support testing, deployment, documentation and client handover.

Required Technical SkillsGenerative AI / LLM

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8+ years of overall experience in Software Engineering / AI / ML.

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Strong hands-on experience with LLMs and Generative AI.

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Experience developing and deploying production-grade GenAI applications.

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Strong understanding of LLM architecture, prompting and model selection.

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Experience with commercial and/or open-source LLMs.

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Strong experience with RAG architectures.

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Experience with embeddings and Vector Databases.

Agentic AI

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Strong hands-on experience building Agentic AI solutions.

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Proven experience with Multi-Agent Orchestration.

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Hands-on experience with one or more

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LangGraph

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LangChain

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AutoGen

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CrewAI

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Equivalent Agentic AI frameworks

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Experience designing agent workflows and state management.

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Strong understanding of tool calling / function calling.

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Experience building agents that interact with APIs, databases and enterprise systems.

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Experience implementing agent guardrails and evaluation mechanisms.

Machine Learning & Statistical Modelling

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Strong foundation in classical Machine Learning.

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Strong understanding of statistics and statistical modelling.

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Experience integrating predictive ML models with GenAI applications.

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Strong Python programming skills.

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Experience with common ML libraries and frameworks.

Enterprise Integration

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Experience integrating AI solutions with ERP and enterprise applications.

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Strong REST API and microservices experience.

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Experience consuming external and real-time data sources.

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Experience developing APIs/tools for AI agents.

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Understanding of enterprise security, authentication and access controls.

Cloud & Engineering

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Strong hands-on Python development.

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Strong software engineering and system-design fundamentals.

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Experience with AWS-based AI/ML architectures.

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AWS Bedrock experience is highly preferred.

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Experience with APIs, microservices and scalable backend systems.

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Understanding of Docker/containerization and CI/CD.

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Experience deploying AI solutions into production environments.

Good to Have

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Procurement / Source-to-Pay / Supply Chain domain experience.

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Procurement analytics or category intelligence experience.

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MCP (Model Context Protocol) experience.

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Real-time event/data processing.

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AWS Bedrock or similar managed GenAI platforms.

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Kafka or other streaming technologies.

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LLM observability and evaluation platforms.

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SAP, Oracle or other ERP integration experience.

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Consulting or client-facing transformation experience.

Ideal Candidate The ideal candidate is a hands-on Senior AI Engineer / AI Architect who can independently design and build a complete Agentic AI solution.

The candidate should have experience in

Classical ML + Statistical Modelling + LLM + RAG + Multi-Agent AI + Enterprise APIs + Cloud + Production Deployment

Candidates with only Prompt Engineering, basic ChatGPT/API integration or simple RAG chatbot development will not be suitable.

Candidates Not to Prioritize

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Basic ChatGPT/API integration profiles.

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Prompt Engineers without strong software engineering experience.

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Candidates with only simple RAG chatbot projects.

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Candidates without Multi-Agent experience.

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Candidates without production GenAI implementation experience.

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Pure Data Scientists without hands-on GenAI engineering.

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Candidates without API/enterprise integration experience.

Technology Split

50% – Classical ML / Statistical Modelling / Analytics

50% – LLM / Generative AI / Agentic AI The LLM/Agentic AI component is particularly critical for this position.

Key Success Criteria The selected candidate should be able to build a production-ready solution capable of:

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Consuming internal, external and real-time data.

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Understanding procurement context.

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Generating category-level business insights.

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Reasoning across multiple information sources.

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Invoking appropriate tools and APIs.

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Integrating with ERP and enterprise systems.

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Recommending or initiating approved business processes.

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Providing users with a simple and actionable experience.

Required Skills

Python | LLM | Generative AI | Agentic AI | Multi-Agent Systems | LangGraph | LangChain | AutoGen | CrewAI | RAG | Vector DB | Machine Learning | Statistical Modelling | REST APIs | AWS | AWS Bedrock | Tool Calling | Enterprise Integration | ERP | Microservices

Work Location & Engagement

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Location: Kolkata

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Work Mode: Onsite / Client-facing

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Experience: 8+ Years

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Budget: Up to ₹3 Lakh/month

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Travel: May be required

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AWS: Preferred / Important