AI Lead Engineer

Location: Pune, MH, in

Company Description

Company Introduction – T-Systems ICT India Pvt. Ltd. T-Systems Information and Communication Technology India Private Limited (T-Systems ICT India Pvt. Ltd.) is a certified Great Place To Work®, proudly recognized for its strong people-first culture and commitment to employee excellence. As a wholly owned subsidiary of T-Systems International GmbH, T-Systems India operates out of Pune and Bangalore, with a dynamic team of over 4,200 professionals delivering high-value IT services to group customers worldwide. T-Systems India plays a key role in this global vision by delivering integrated, end-to-end IT solutions and sector-specific software to drive transformation across industries, including automotive, manufacturing, logistics, transportation, healthcare, and the public sector. For over 25 years, T-Systems International GmbH has been at the forefront of digital innovation, driving progress and fostering digital optimism. As a leading European IT services provider and a proud part of Deutsche Telekom, T-Systems delivers transformative digitalization projects backed by deep expertise in consulting, cloud, AI, cybersecurity, and connectivity. With a global workforce of 26,000 employees across 26 countries, we set industry benchmarks in efficiency, sovereignty, security, and reliability—empowering organizations to unlock their full digital potential. With annual revenues exceeding EUR 4.0 billion (2024), T-Systems stands as one of Europe’s foremost digital transformation partners, committed to shaping the future of enterprise technology.

Job Description

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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