T-Systems ICT India

AI Lead Engineer

Pune, MH, India · On-site · Full-time

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EmployerT-Systems ICT India
LocationPune, MH, 411045, India
Work styleOn-site
Employment typeFull-time
Employer posted26 days ago

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.

Show full description

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.

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