TCS is Hiring : Gen Ai with LLM - Walk-ins in Multiple Locations

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TCS Is Hiring Experienced candidates for the role Gen Ai with LLM. The details of the job, requirements and other information given below:

Table of Contents

TCS Is Hiring : Gen Ai with LLM

  • Exp req: 4to 15 yrs
  • Interview Location 1 : Tata Consultancy Services, Millennium Towers A & B, IT Hill No. 3, Rushikonda, Visakhapatnam, Andhra Pradesh – 530045, India.
  • Interview Location 2 : L‑Centre, Unit VI, No. 78, 79 & 83, L‑Centre, EPIP Industrial Estate (Vydehi RC‑1 Block), Whitefield, Bengaluru, Karnataka – 560066, India.

  • Interview Location 3 : Magnum IG3 Infra Limited, Pallavaram – Thoraipakkam, 200 Feet Road, Thoraipakkam, Chennai, Tamil Nadu – 600097, India.

    Required Skills:

  • Degree in computer science, artificial intelligence, or IT.
  • Strong knowledge of Generative AI concepts including foundation models / LLMs, embeddings, and NLP fundamentals used in GenAI solutions.
  • Design, implement, and optimize GenAI applications (LLM-powered services) for real business use-cases, with focus on accuracy, efficiency, and scalability.
  • Hands-on prompt engineering (e.g., zero/few-shot, Chain-of-Thought, Tree-of-Thought, prompt templates) and ability to evaluate and refine prompts based on output quality.
  • Build Retrieval-Augmented Generation (RAG) solutions, including retrieval strategy integration and prompt + retrieval orchestration patterns.
  • Experience with agent / app evaluation practices—evaluate model and agent performance for GenAI use-cases (quality, effectiveness, benchmarking).
  • Cloud-based GenAI platform experience (e.g., AWS / Azure / GCP) for building and deploying scalable GenAI solutions with high availability and performance.
  • MLOps / LLMOps-aligned practices: CI/CD, monitoring, logging, and version control for deploying and operating GenAI systems in production.
  • Proficiency in programming languages such as Python, .Net or Java, with experience in relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Keras).

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