Capgemini Technology Services
AI/ML Engineer - Generative AI
AI/ML Engineer at Capgemini in Kolkata building generative AI applications: developing LLM-powered apps and RAG pipelines, prompt engineering and fine-tuning (LoRA/QLoRA), building REST APIs, and deploying/monitoring AI solutions on cloud platforms (GCP/AWS/Azure) using Python and containerized environments.
- Compensation
- Not disclosed
- Location
- Kolkata
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Ml / AI
- Posted
Skills
Must have
- Minimum 5+ years of overall experience
- Strong hands-on experience in Machine Learning using at least one cloud platform: GCP, AWS, or Azure (candidates without hands-on cloud experience not considered)
Nice to have
- GCP experience is a significant advantage
- 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
Full description
Job Description : Role & Responsibilities : Requirements :
- Minimum 5+ years of overall experience.
- Strong hands-on experience in Machine Learning using at least one cloud platform : GCP, AWS, or Azure.
- Candidates without hands-on cloud experience should not be considered for the interview.
- GCP experience will be a significant advantage.
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.