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

- Lead architecture and development of enterprise-grade LLM, GenAI and Agentic AI solutions.
- Design and implement Multi-Agent AI workflows capable of reasoning, planning and executing multi-step tasks.
- Build and orchestrate specialized AI agents for procurement-related use cases.
- Design agent workflows, state management, tool calling and API integrations.
- Develop the Procurement Category Insights Engine using ML, statistical modelling and GenAI.
- Integrate internal, external and real-time data sources.
- Integrate AI solutions with ERP and enterprise applications.
- Build tools/API layers that enable agents to retrieve information and perform approved business actions.
- Develop RAG-based solutions for enterprise knowledge and contextual understanding.
- Implement prompt engineering, agent instructions, guardrails and evaluation mechanisms.
- Implement LLM monitoring, evaluation and performance optimization.
- Integrate classical ML/statistical models with GenAI applications.
- Work closely with Data Scientists, Backend Engineers and Frontend Engineers to deliver end-to-end solutions.
- Ensure solutions are scalable, secure, reliable and production-ready.
- Lead technical discussions with client stakeholders.
- Support testing, deployment, documentation and client handover.

Required Technical SkillsGenerative AI / LLM

- 8+ years of overall experience in Software Engineering / AI / ML.
- Strong hands-on experience with LLMs and Generative AI.




- Experience developing and deploying production-grade GenAI applications.
- Strong understanding of LLM architecture, prompting and model selection.
- Experience with commercial and/or open-source LLMs.
- Strong experience with RAG architectures.
- Experience with embeddings and Vector Databases.

Agentic AI
- Strong hands-on experience building Agentic AI solutions.
- Proven experience with Multi-Agent Orchestration.
- Hands-on experience with one or more:
- LangGraph
- LangChain
- AutoGen
- CrewAI
- Equivalent Agentic AI frameworks

- Experience designing agent workflows and state management.
- Strong understanding of tool calling / function calling.
- Experience building agents that interact with APIs, databases and enterprise systems.
- Experience implementing agent guardrails and evaluation mechanisms.

Machine Learning & Statistical Modelling
- Strong foundation in classical Machine Learning.
- Strong understanding of statistics and statistical modelling.
- Experience integrating predictive ML models with GenAI applications.
- Strong Python programming skills.
- Experience with common ML libraries and frameworks.

Enterprise Integration
- Experience integrating AI solutions with ERP and enterprise applications.
- Strong REST API and microservices experience.
- Experience consuming external and real-time data sources.
- Experience developing APIs/tools for AI agents.
- Understanding of enterprise security, authentication and access controls.

Cloud & Engineering
- Strong hands-on Python development.
- Strong software engineering and system-design fundamentals.
- Experience with AWS-based AI/ML architectures.
- AWS Bedrock experience is highly preferred.
- Experience with APIs, microservices and scalable backend systems.
- Understanding of Docker/containerization and CI/CD.
- Experience deploying AI solutions into production environments.

Good to Have
- Procurement / Source-to-Pay / Supply Chain domain experience.
- Procurement analytics or category intelligence experience.




- MCP (Model Context Protocol) experience.
- Real-time event/data processing.
- AWS Bedrock or similar managed GenAI platforms.
- Kafka or other streaming technologies.
- LLM observability and evaluation platforms.
- SAP, Oracle or other ERP integration experience.
- 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

- Basic ChatGPT/API integration profiles.
- Prompt Engineers without strong software engineering experience.
- Candidates with only simple RAG chatbot projects.
- Candidates without Multi-Agent experience.
- Candidates without production GenAI implementation experience.
- Pure Data Scientists without hands-on GenAI engineering.
- 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:

- Consuming internal, external and real-time data.
- Understanding procurement context.
- Generating category-level business insights.
- Reasoning across multiple information sources.
- Invoking appropriate tools and APIs.
- Integrating with ERP and enterprise systems.
- Recommending or initiating approved business processes.
- 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

- Location: Kolkata
- Work Mode: Onsite / Client-facing
- Experience: 8+ Years
- Budget: Up to ₹3 Lakh/month
- Travel: May be required
- AWS: Preferred / Key

Skills: aws,gen ai,machine learning

📌 Lead LLM / Agentic AI Engineer – AI-Led Procurement Transformation (Kolkata)
🏢 Zorba AI
📍 Kolkata