Role Summary

We are seeking an AI / ML Solutions Lead with proven hands-on experience in Agentic AI, Large Language Models (LLMs), and enterprise-grade Machine Learning delivery. In this leadership role, you will own the complete AI solutions lifecycle—from opportunity identification and solution architecture to production deployment and continuous improvement.

You will lead and mentor AI/ML engineers, collaborate directly with clients to define AI transformation roadmaps, and drive pre-sales, solution design, and successful delivery across enterprise engagements. Experience in Finance (AP/AR, P2P, Cash Flow) or Supply Chain Management (Procurement, Inventory, Logistics) domains will be considered a strong advantage.

Key Responsibilities

• Own the complete AI/ML solutions lifecycle from discovery, architecture, development, deployment, and hypercare.
  


• Design and deliver Agentic AI solutions using LangGraph, AutoGen, CrewAI, or similar frameworks.
  


• Build enterprise-grade RAG pipelines, multi-agent systems, and LLM fine-tuning solutions.
  


• Participate in pre-sales activities including solution design, PoCs, RFP/RFQ responses, and client presentations.
  


• Define AI transformation strategies and advise clients on implementation, feasibility, and ROI.
  


• Lead, mentor, and manage a team of AI/ML engineers while ensuring technical excellence and delivery quality.
  


• Collaborate with business analysts, delivery managers, and product teams to build scalable AI architectures.
  


• Drive MLOps practices including model monitoring, versioning, retraining, and Responsible AI.
  


• Implement AI solutions for Finance and Supply Chain Management use cases where applicable.
  


• Develop reusable AI accelerators, frameworks, and contribute to the organization's AI Center of Excellence.
  


• Stay updated with the latest advancements in Agentic AI, Generative AI, and Machine Learning technologies.
  

Required Skills

Core AI / Machine Learning

• Advanced Python
  


• Machine Learning
  


• Deep Learning (TensorFlow / PyTorch)
  


• NLP & Text Analytics
  


• Feature Engineering
  


• Model Evaluation & Hyperparameter Tuning
  


• Statistics & Probability
  


• Data Pipelines
  


• ML Pipeline Architecture
  

Large Language Models & Generative AI

• GPT-4o, Claude, Gemini integration
  


• Prompt Engineering
  


• Retrieval-Augmented Generation (RAG)
  


• Vector Databases (FAISS, Pinecone, Weaviate)
  


• LangChain / LlamaIndex
  


• Fine-Tuning (LoRA, QLoRA, PEFT)
  


• Embeddings & Semantic Search
  


• Knowledge Base Design
  


• LLM Evaluation Frameworks
  

Agentic AI

• Agent Architecture Design
  


• LangGraph
  


• AutoGen
  


• CrewAI
  


• Tool Use & Function Calling
  


• ReAct / Chain of Thought / Plan-and-Execute
  


• Multi-Agent Systems
  


• Memory & State Management
  


• Human-in-the-Loop Workflows
  


• AI Guardrails & Safety
  


• Production Deployment
  

Data & Infrastructure

• FastAPI / Flask
  


• REST APIs
  


• SQL & NoSQL
  


• Azure / AWS / GCP
  


• Docker
  


• Git
  


• MLOps Fundamentals
  

Leadership & Consulting

• AI Solution Architecture
  


• Client Stakeholder Management
  


• Team Leadership & Mentoring
  


• Delivery Governance
  


• Agile / Scrum
  


• Risk Management
  


• Proposal Writing
  


• Estimation & Pre-sales Support
  

Preferred Skills

• MLflow, Weights & Biases, Model Registry
  


• Hugging Face Transformers & PEFT
  


• Azure OpenAI Service, Copilot Studio, Semantic Kernel
  


• UiPath & Power Automate
  


• Knowledge Graphs (Neo4j, Graph RAG)
  


• Streamlit, Gradio, Chainlit
  


• Kubernetes, Helm, Azure Functions, AWS Lambda
  


• Whisper, OpenCV, CLIP, GPT-4 Vision
  


• Explainable AI (SHAP/LIME), AI Governance & Responsible AI
  


• Experience in Finance (AP/AR, P2P, Invoice Processing) or Supply Chain Management (Procurement, Inventory, Demand Forecasting)
  

Qualifications

• Education: B.E./B.Tech./M.Tech in Computer Science, Data Science, Electronics, or related field. MBA is an advantage.
  


• Experience: 7–9 years overall experience with 2–3 years in AI/ML leadership, solution architecture, or technical leadership.
  


• Proven experience delivering Agentic AI and LLM-based enterprise solutions.
  


• Finance or Supply Chain domain experience is preferred.
  


• AWS/Azure AI certifications, Google Professional ML Engineer, or equivalent certifications are an added advantage.
  

Work Model

• Location: India
  


• Employment Type: Full-Time
  


• Work Mode: WFO / Remote / Hybrid (based on project requirements and candidate profile)
  


• High-visibility leadership role with direct interaction with senior stakeholders.
  


• Opportunity to contribute to and shape the organization's AI Centre of Excellence (CoE).
  

Requirements