Company Description

T-Systems Information and Communication Technology India Private Limited (T-Systems ICT India Pvt. Ltd.) is a proud recipient of the prestigious Great Place To Work® Certification™. As a wholly owned subsidiary of T-Systems International GmbH, T-Systems India operates across Pune, Bangalore, and Nagpur, boasting a dedicated team of 3500+ employees providing services to group customers. T-Systems offers integrated end-to-end IT solutions, driving the digital transformation of companies in all industries, including automotive, manufacturing, logistics, and transportation, as well as healthcare and the public sector. T-Systems develops vertical, company-specific software solutions for these sectors. T-Systems International GmbH is an information technology and digital transformation company with a presence in over 20 countries and a revenue of more than €4 billion. T-Systems is a world-leading provider of digital services and has over 20 years of experience in the transformation and management of IT systems. As a subsidiary of Deutsche Telekom and a market leader in Germany, T-Systems International offers secure, integrated information technology and digital solutions from a single source.

Job Description

Experience: 8+ Years

Location: Balewadi Highstreet, Pune

Mode of Work: Hybrid

• 8+ years of overall experience in machine learning and deep learning, with 2+ years focused on Large Language Models (LLMs) and Generative AI.
• Practical knowledge of Natural Language Processing (NLP) use cases
• Expertise in Retrieval-Augmented Generation (RAG) techniques, including ingestion techniques, parsing/chunking strategies, reranking, embedding, and vector databases. Proficient in retrieval strategies such as hybrid, BM25, keyword, semantic, and metadata filtering.
• Strong background in prompt engineering, including system prompts and context prompting to enhance model interactions and outputs.
• Experience with evaluation techniques for both generation and retrieval.
• Knowledge of ethical AI practices, including guardrails to prevent prompt injections and ensure responsible AI usage.
• Familiarity with frameworks such as Langchain, Llama-index, and NeMo for building robust AI applications.
• Understanding of agent-based systems like CrewAI and Langgraph for enhanced AI capabilities