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.

Please Note: Fraudulent job postings/job scams are increasingly common. Beware of misleading advertisements and fraudulent communication issuing 'offer letters' on behalf of T-Systems in exchange for a fee. Please look for an authentic T-Systems email id - [email removed].

Stay vigilant. Protect yourself from recruitment fraud!

To know more please visit : Fraud Alert