Walk-in | Generative AI Developer

Tata Consultancy Services; Chennai District; On-site; INR 2,000,000 - 3,200,000; Full time

Job summary

Tata Consultancy Services in Chennai is seeking a Gen AI Developer with strong GenAI expertise to design, implement, and optimize LLM-powered services for real business use cases. You will work on prompt engineering, RAG strategies, and production-grade ML operations within a scalable cloud environment.

The role emphasizes embedding AI concepts, model evaluation, and cross-functional collaboration to deliver high-quality GenAI solutions in a fast-paced setting.

Qualifications

• Strong knowledge of Generative AI concepts including foundation models, embeddings, and NLP fundamentals.
• Experience designing and deploying LLM-powered services for real business use-cases.
• Hands-on prompt engineering and evaluation to improve output quality.
• Experience with Retrieval-Augmented Generation (RAG) and retrieval orchestration.
• MLOps / LLMOps practices: CI/CD, monitoring, and version control.
• Proficiency in Python, .Net or Java with TensorFlow/PyTorch/Keras.

Responsibilities

• Design, implement, and optimize GenAI applications (LLM-powered services) for real business use-cases, with focus on accuracy, efficiency, and scalability.
• Build and evaluate retrieval-augmented generation (RAG) solutions and integration patterns.
• Implement robust MLOps practices for production GenAI systems including CI/CD, monitoring, and version control.
• Collaborate on cloud-based GenAI platform deployments (AWS/Azure/GCP) ensuring high availability and performance.

Skills

GenAI concepts

Prompt engineering

RAG solutions

Model evaluation & benchmarking

MLOps / LLMOps

Cloud platforms (AWS/Azure/GCP)

Programming (Python/Java/.Net)

Tools

TensorFlow

PyTorch

Keras

Job description

Greetings from TCS!!!

Come and join us for an exciting career with TCS!!!

Role: Gen AI Developer

Desired Experience Range: 4-15 Years

Location: Chennai

Required Skills & Experience:

• 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 practicesevaluate 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).