Python Developer - Rest API + LLM | Pune | 8 to 12 Years
Capgemini
Python Developer - Rest API + LLM | Pune | 8 to 12 Years
Job Description
Python Developer - Rest API + LLM | Pune | 8 to 12 Years
📋 Job Overview
Capgemini is seeking a Python Developer with 8-12 years of experience, specializing in AI, RAG integration, and MCP for building scalable applications and intelligent systems. The role involves developing Python applications, implementing RAG pipelines with LLMs, and creating MCP-based integrations for enterprise data and conversational AI. Responsibilities include optimizing performance, collaborating with teams, and staying current with AI technologies in Pune.
📍 Location: Pune
💼 Experience Level: Experienced Professionals
🏢 Business Unit: FS
🎯 Key Responsibilities
- Design, develop, and maintain applications in Python
- Implement RAG pipelines by integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.) with enterprise and external data sources
- Develop MCP-based integrations to connect tools, APIs, and enterprise data systems with LLMs
- Build APIs and microservices for AI-powered search, summarization, and conversational AI
- Create document ingestion pipelines (PDFs, databases, SharePoint, etc.) and manage embeddings with vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.)
- Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG/MCP solutions
- Optimize application performance, security, and scalability for production-grade AI systems
- Stay updated with AI frameworks, MCP standards, and cloud AI services
✅ Required Qualifications
- Minimum of 8 years of IT experience with 1+ years of AI experience
⭐ Preferred Qualifications
- Experience with containerization (Docker, Kubernetes)
- Experience with cloud AI services (Azure, AWS, GCP) for deployment and scaling
- Exposure to SQL/NoSQL databases for structured and unstructured data
- Prior experience in chatbot development, enterprise search, or knowledge management systems
- Understanding of MLOps practices for AI model deployment and monitoring
🛠️ Required Skills
- Python
- OOP
- REST APIs
- Microservices architecture
- LLM-based applications
- RAG (Retrieval-Augmented Generation) integration
- Model Context Protocol (MCP) for AI tool orchestration
- Vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search)
- LangChain
- LlamaIndex
- Hugging Face Transformers
- AI libraries
- Problem-solving
- Cross-functional collaboration
Locations
- Pune, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Pythonintermediate
- OOPintermediate
- REST APIsintermediate
- Microservices architectureintermediate
- LLM-based applicationsintermediate
- RAG (Retrieval-Augmented Generation) integrationintermediate
- Model Context Protocol (MCP) for AI tool orchestrationintermediate
- Vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search)intermediate
- LangChainintermediate
- LlamaIndexintermediate
- Hugging Face Transformersintermediate
- AI librariesintermediate
- Problem-solvingintermediate
- Cross-functional collaborationintermediate
Required Qualifications
- Minimum of 8 years of IT experience with 1+ years of AI experience (experience)
Preferred Qualifications
- Experience with containerization (Docker, Kubernetes) (experience)
- Experience with cloud AI services (Azure, AWS, GCP) for deployment and scaling (experience)
- Exposure to SQL/NoSQL databases for structured and unstructured data (experience)
- Prior experience in chatbot development, enterprise search, or knowledge management systems (experience)
- Understanding of MLOps practices for AI model deployment and monitoring (experience)
Responsibilities
- Design, develop, and maintain applications in Python
- Implement RAG pipelines by integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.) with enterprise and external data sources
- Develop MCP-based integrations to connect tools, APIs, and enterprise data systems with LLMs
- Build APIs and microservices for AI-powered search, summarization, and conversational AI
- Create document ingestion pipelines (PDFs, databases, SharePoint, etc.) and manage embeddings with vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.)
- Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG/MCP solutions
- Optimize application performance, security, and scalability for production-grade AI systems
- Stay updated with AI frameworks, MCP standards, and cloud AI services
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Python Developer - Rest API + LLM | Pune | 8 to 12 Years
Capgemini
Python Developer - Rest API + LLM | Pune | 8 to 12 Years
Job Description
Python Developer - Rest API + LLM | Pune | 8 to 12 Years
📋 Job Overview
Capgemini is seeking a Python Developer with 8-12 years of experience, specializing in AI, RAG integration, and MCP for building scalable applications and intelligent systems. The role involves developing Python applications, implementing RAG pipelines with LLMs, and creating MCP-based integrations for enterprise data and conversational AI. Responsibilities include optimizing performance, collaborating with teams, and staying current with AI technologies in Pune.
📍 Location: Pune
💼 Experience Level: Experienced Professionals
🏢 Business Unit: FS
🎯 Key Responsibilities
- Design, develop, and maintain applications in Python
- Implement RAG pipelines by integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.) with enterprise and external data sources
- Develop MCP-based integrations to connect tools, APIs, and enterprise data systems with LLMs
- Build APIs and microservices for AI-powered search, summarization, and conversational AI
- Create document ingestion pipelines (PDFs, databases, SharePoint, etc.) and manage embeddings with vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.)
- Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG/MCP solutions
- Optimize application performance, security, and scalability for production-grade AI systems
- Stay updated with AI frameworks, MCP standards, and cloud AI services
✅ Required Qualifications
- Minimum of 8 years of IT experience with 1+ years of AI experience
⭐ Preferred Qualifications
- Experience with containerization (Docker, Kubernetes)
- Experience with cloud AI services (Azure, AWS, GCP) for deployment and scaling
- Exposure to SQL/NoSQL databases for structured and unstructured data
- Prior experience in chatbot development, enterprise search, or knowledge management systems
- Understanding of MLOps practices for AI model deployment and monitoring
🛠️ Required Skills
- Python
- OOP
- REST APIs
- Microservices architecture
- LLM-based applications
- RAG (Retrieval-Augmented Generation) integration
- Model Context Protocol (MCP) for AI tool orchestration
- Vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search)
- LangChain
- LlamaIndex
- Hugging Face Transformers
- AI libraries
- Problem-solving
- Cross-functional collaboration
Locations
- Pune, India
Salary
Estimated Salary Rangemedium confidence
2,500,000 - 4,200,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- Pythonintermediate
- OOPintermediate
- REST APIsintermediate
- Microservices architectureintermediate
- LLM-based applicationsintermediate
- RAG (Retrieval-Augmented Generation) integrationintermediate
- Model Context Protocol (MCP) for AI tool orchestrationintermediate
- Vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search)intermediate
- LangChainintermediate
- LlamaIndexintermediate
- Hugging Face Transformersintermediate
- AI librariesintermediate
- Problem-solvingintermediate
- Cross-functional collaborationintermediate
Required Qualifications
- Minimum of 8 years of IT experience with 1+ years of AI experience (experience)
Preferred Qualifications
- Experience with containerization (Docker, Kubernetes) (experience)
- Experience with cloud AI services (Azure, AWS, GCP) for deployment and scaling (experience)
- Exposure to SQL/NoSQL databases for structured and unstructured data (experience)
- Prior experience in chatbot development, enterprise search, or knowledge management systems (experience)
- Understanding of MLOps practices for AI model deployment and monitoring (experience)
Responsibilities
- Design, develop, and maintain applications in Python
- Implement RAG pipelines by integrating LLMs (OpenAI, Azure OpenAI, Hugging Face, LangChain, LlamaIndex, etc.) with enterprise and external data sources
- Develop MCP-based integrations to connect tools, APIs, and enterprise data systems with LLMs
- Build APIs and microservices for AI-powered search, summarization, and conversational AI
- Create document ingestion pipelines (PDFs, databases, SharePoint, etc.) and manage embeddings with vector databases (Pinecone, Weaviate, FAISS, Qdrant, Azure Cognitive Search, etc.)
- Collaborate with AI engineers, architects, and data teams to ensure scalable deployment of RAG/MCP solutions
- Optimize application performance, security, and scalability for production-grade AI systems
- Stay updated with AI frameworks, MCP standards, and cloud AI services
Tags & Categories
Answer 10 quick questions to check your fit for Python Developer - Rest API + LLM | Pune | 8 to 12 Years @ Capgemini.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs