AI Lead Engineer

Role Overview - AI Lead Engineer (GenAI & Agentic AI)

Location - Pune / Hyderabad

Experience: 10-15 Years (including 3-5 years in AI/ML Generative AI or Agentic AI Solutions)

Role Overview

We are looking for an experienced AI Lead Engineer to drive the design architecture and delivery of enterprise-grade AI solutions leveraging Generative AI Large Language Models (LLMs) Retrieval-Augmented Generation (RAG) and Agentic AI frameworks. The ideal candidate will have a strong software engineering background combined with expertise in AI solution design AI agent orchestration cloud platforms and modern MLOps practices.

Key Responsibilities

• Lead the design architecture and implementation of AI/GenAI solutions.
• Build and deploy scalable LLM-powered applications and RAG systems.
• Design and implement Agentic AI and Multi-Agent systems for business automation and intelligence.
• Define enterprise AI architecture governance security and best practices.
• Collaborate with business stakeholders product teams and engineering teams to deliver AI solutions.
• Mentor development teams and drive AI innovation initiatives.
• Evaluate emerging AI technologies and recommend adoption strategies.

Technical Skills

• Strong expertise in AI Solution Architecture & Design.
• Strong programming skills in Python and Temporal.
• Experience with TensorFlow PyTorch Scikit-learn (preferred).
• Expertise in Generative AI LLMs RAG Vector Databases AI Agents and Multi-Agent Systems.
• Hands-on experience with LangChain LlamaIndex Semantic Kernel LangGraph CrewAI AutoGen or similar frameworks.
• Strong understanding of Prompt Engineering Fine-Tuning Embeddings and RAG Optimization.
• Experience with Azure OpenAI OpenAI GPT Models Claude Gemini Llama Mistral or equivalent foundation models.
• Knowledge of Model Context Protocol (MCP) Tool Calling Function Calling and Agent Orchestration.
• Experience with Pinecone Qdrant Weaviate ChromaDB FAISS Azure AI Search or similar vector databases.
• Experience with Azure AI Services Azure OpenAI AWS AI/ML Services or Google Vertex AI.
• Strong understanding of MLOps/LLMOps practices using MLflow Kubeflow Databricks Azure ML etc.
• Experience with APIs microservices Docker Kubernetes and cloud-native architectures.
• Knowledge of SQL NoSQL databases and data engineering concepts.
• Experience with AI monitoring observability evaluation frameworks and governance practices.

Preferred Qualifications

• Experience in GraphRAG Knowledge Graphs and Enterprise Search solutions.
• Exposure to AI governance compliance and Responsible AI practices.
• Experience leading AI transformation initiatives and customer-facing engagements.

Additional Information :

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Remote Work :

No

Employment Type :

Full-time