About this role
We are looking for a python developer with minimum 6-8 years specializing in Retrieval-Augmented Generation (RAG) systems, with experience in large language models (LLMs), vector databases, and cloud-based microservices. Your role will focus on building, integrating, and optimizing LLM workflows using LangChain and managing complex infrastructure with AWS services like Lambda and ECS. You'll bring expertise in containerized environments, using Docker, and work with vector databases to power data-driven applications.
You'll have opportunity to:
• RAG Workflow Development: Design and deploy LLM-driven RAG workflows using LangChain and vector databases to provide high-accuracy data retrieval and enhanced content generation.
• Vector Database Management: Integrate and manage vector databases like Qdrant for optimized, high-speed vector searches and data retrieval.
• Cloud Computing: Use AWS services, including Lambda and ECS, to build serverless architectures and scalable containerized applications.
• API & Backend Development: Build APIs with FastAPI and Uvicorn to support low-latency interactions and handle high traffic volumes.
• Monitoring & Observability: Implement observability best practices using Datadog, ddtrace, and logging tools to maintain performance and troubleshoot complex workflows.
• Proficiency in LLM and RAG Workflows: experience with LangChain and vector databases, applying RAG techniques for intelligent data retrieval and generation.
• Python Proficiency (>=3.11, <3.12): Advanced Python skills, including experience with asynchronous programming.
• Proficient in AWS environment
• Understanding of MCP Server
Location Requirement
This role is based in Hyderabad and follows a hybrid work model (2 days onsite per week)
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