Company Name

Capgemini Technology Services India Limited ( Pune )

Job Description

• Job Description
  • Works in the area of Software Engineering, which encompasses the development, maintenance and optimization of software solutions/applications.
  • Applies scientific methods to analyse and solve software engineering problems.
  • He/she is responsible for the development and application of software engineering practice and knowledge, in research, design, development and maintenance.
  • His/her work requires the exercise of original thought and judgement and the ability to supervise the technical and administrative work of other software engineers.
  • The software engineer builds skills and expertise of his/her software engineering discipline to reach standard software engineer skills expectations for the applicable role, as defined in Professional Communities.
  • The software engineer collaborates and acts as team player with other software engineers and stakeholders.
  Job Description - Grade Specific
  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 Skills & Experience:
  • Minimum of 8 years of IT experience with 1+ years of AI experience
  • Strong hands-on experience in Python.
  • Solid understanding of OOP, REST APIs, and microservices architecture.
  • Proven experience with LLM-based applications and RAG (Retrieval-Augmented Generation) integration.
  • Knowledge and practical implementation of Model Context Protocol (MCP) for AI tool orchestration.
  • Familiarity with vector databases (FAISS, Pinecone, Weaviate, Qdrant, Azure Cognitive Search).
  • Hands-on experience with LangChain, LlamaIndex, Hugging Face Transformers, or similar AI libraries.
  • Strong problem-solving and cross-functional collaboration skills.
  Good to Have Skills
  • 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.

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