Developer

Tata Consultancy Services; Hyderabad; On-site; INR 1,800,000 - 3,200,000; Full time

Job summary

Tata Consultancy Services is seeking a seasoned AI engineer to design and implement Gen AI, LLM, and agentic AI solutions. You will develop scalable ML/NLP models, integrate with LangChain/LlamaIndex, and build end-to-end pipelines.

The role demands hands-on work with RAG architectures, APIs, and cloud deployment across Azure, AWS, and GCP. Ideal candidates have 4–8 years of relevant experience, strong Python programming, and deep knowledge of DL/ML/NLP, with concrete project history in LLMs and

Qualifications

• Bachelor’s or master’s degree in computer science, AI, data science, or related field.
• Strong programming skills in Python with ML/NLP focus.
• Hands-on experience with Deep Learning, ML and NLP.
• Experience with LLMs (GPT, Gemini, LLaMA, Mistral) and RAG architecture.
• Expert-level proficiency with LangChain and/or LlamaIndex for building complex LLM apps, including chains, agents, memory, and tool integration.

Skills

Python

Deep Learning

NLP

LLMs

RAG pipelines

LangChain

LlamaIndex

APIs (FastAPI)

CI/CD

Cloud (Azure/GCP/AWS)

Data structures

Algorithms

Education

Bachelor's or Master's in CS/AI/Data Science

Tools

FastAPI

REST API design

CI/CD pipelines

Azure

GCP

AWS

Job description

• Required Technical Skill: Gen AI / LLM /Agentic AI
• Experience: 4 to 8 Years
• Strong programming skills in Python with experience in building ML/NLP applications.
• Hands-on experience with Deep Learning, Machine Learning, and Natural Language Processing.
• Proficiency in working with LLMs (e.g., GPT,Gemini, LLaMA, Mistral) and RAG architecture.
• Experience with Agentic AI frameworks and autonomous agent design.
• Familiarity with FastAPI for building RESTful APIs.
• Experience with CI/CD pipelines and deploying solutions on Azure Cloud, GCP and AWS
• Solid understanding of data structures, algorithms, and software engineering principles.
• Bachelor’s or master’s degree in computer science, AI, Data Science, or related field.
• Retrieval Augmented Generation (RAG): Hands-on experience in building and optimizing RAG pipelines from scratch
• Expert-level proficiency and hands-on experience with LangChain and/or LlamaIndex for building complex LLM applications, including chains, agents, memory, and tool integration.