F2F Drive | Gen Ai | Gurgaon

Capgemini; Gurugram District; Hybrid; INR 1,800,000 - 2,800,000; Full time

Job summary

Capgemini is seeking a capable AI engineer to develop and enhance Generative AI applications using LLMs and AI frameworks in a Gurgaon-based role. You will build RAG pipelines, vector search, and AI-powered workflows, while designing prompts and fine-tuning models with LoRA/QLoRA.

You will deploy, monitor, and maintain AI solutions in cloud and containerized environments and ensure code quality with tests and reviews.

Qualifications

• Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
• Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
• Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
• Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
• Experience with PyTorch, TensorFlow, or Keras.
• Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
• Understanding of AI governance, data privacy, and Responsible AI principles.

Responsibilities

• Develop and enhance Generative AI applications using LLMs and AI frameworks.
• Build and optimize RAG pipelines, vector search, and AI-powered workflows.
• Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
• Develop REST APIs and integrate AI capabilities into enterprise applications.
• Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
• Ensure code quality through testing, debugging, documentation, and code reviews.
• Follow Responsible AI, security, and data governance practices.

Skills

Python

APIs

Debugging

DS & Algorithms

LLMs

Prompt engineering

RAG

Embeddings

LangChain

LangGraph

LlamaIndex

Hugging Face

Vector search

PyTorch

TensorFlow

Keras

Docker

Git

CI/CD

Azure

AWS

GCP

Responsible AI

Data privacy

Tools

Docker

Git

CI/CD

Azure

AWS

GCP

LangChain

LlamaIndex

Hugging Face

Job description

Role & responsibilities

Your Role

• Develop and enhance Generative AI applications using LLMs and AI frameworks.
• Build and optimize RAG pipelines, vector search, and AI-powered workflows.
• Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
• Develop REST APIs and integrate AI capabilities into enterprise applications.
• Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
• Ensure code quality through testing, debugging, documentation, and code reviews.
• Follow Responsible AI, security, and data governance practices.

Preferred candidate profile

• Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
• Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
• Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
• Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
• Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
• Experience with PyTorch, TensorFlow, or Keras.
• Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
• Understanding of AI governance, data privacy, and Responsible AI principles.