1 day ago
Pune, India +3 moreSenior
Responsibilities
- Design and develop Generative AI solutions using Python, LLMs, RAG, and agentic AI frameworks.
- Build intelligent AI agents with LangChain, LangGraph, and vector databases.
- Develop and optimize ETL pipelines, data ingestion, and retrieval workflows for AI applications.
- Deploy, monitor, and scale AI/ML solutions on AWS, Azure, or GCP using MLOps and LLMOps practices.
- Collaborate with business and engineering teams to deliver production-grade AI applications.
Requirements
- Strong experience in Python development and backend engineering.
- Hands-on experience with LLMs, RAG, agentic AI, LangChain, LangGraph, and vector databases.
- Strong knowledge of SQL, data engineering, ETL, and data processing frameworks.
- Experience with AWS, Azure, or GCP and AI deployment pipelines.
- Familiarity with MLOps, LLMOps, model monitoring, evaluation, and performance optimization.
Benefits
- Career paths and internal opportunities across the Capgemini group, with personalized career guidance from company leaders.
- Comprehensive wellness benefits including health checks, telemedicine, insurance with top-ups, elder care, partner coverage, and new parent support via flexible work.
- Opportunities to work on technology and engineering projects with industry leaders and on societal and environmental challenges.
Tech Stack
Categories
About Capgemini
Capgemini is a global IT services and consulting firm that delivers strategy, cloud, AI, software engineering, and managed services to large enterprises and public-sector clients. Founded in 1967 and headquartered in Paris, it is publicly traded on Euronext Paris and operates in 50+ countries. The group expanded its engineering capabilities by acquiring Altran in 2020, now operating as Capgemini Engineering.