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Large Language Model (LLM) Engineer

Large Language Model (LLM) Engineer

Tata Consultancy ServicesAhmedabad, Republic Of India, IN
1 day ago
Job description

Total Exp : 4 to 8 Years

Location : PAN India

Skill : Gen AI Developer

Desired Skills :

  • 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.

Roles and Responsibilites :

  • Design and implement GenAI solutions leveraging LLMs, RAG pipelines, and Agentic AI architectures.
  • Develop and fine-tune deep learning models for NLP tasks using frameworks like PyTorch or TensorFlow.
  • Build scalable APIs using FastAPI to serve AI models and integrate with enterprise systems.
  • Collaborate with data scientists and ML engineers to deploy models using CI / CD pipelines on Azure.
  • Optimize model performance and ensure robustness in production environments.
  • Stay updated with the latest research and advancements in generative AI and deep learning.
  • Scalability & Performance : Ability to write efficient code and consider scalability and latency implications for Gen AI applications.
  • Containerization : Practical experience with Docker for packaging and deploying applications.

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