Python Langchain Lead

Happiest Minds Technologies; Hyderabad; Hybrid; INR 4,000,000 - 7,000,000; Full time

Job summary

Happiest Minds Technologies in Hyderabad invites an experienced Python-Langchain Lead to architect and scale RAG-driven data workflows. You will leverage LangChain, LLMs, and vector databases to deliver high-accuracy retrieval and content generation at scale.

Responsibilities include building and optimizing AWS-based microservices, containerized apps with Docker, and API services using FastAPI/Uvicorn, while ensuring observability with Datadog and ddtrace across complex data pipelines.

Qualifications

• Experience with LangChain and vector databases, applying RAG techniques for intelligent data retrieval and generation.

Responsibilities

• Design and deploy LLM-driven RAG workflows using LangChain and vector databases to provide high-accuracy data retrieval and enhanced content generation.
• Integrate and manage vector databases like Qdrant for optimized, high-speed vector searches and data retrieval.
• Use AWS services, including Lambda and ECS, to build serverless architectures and scalable containerized applications.
• Build APIs with FastAPI and Uvicorn to support low-latency interactions and handle high traffic volumes.
• Implement observability best practices using Datadog, ddtrace, and logging tools to maintain performance and troubleshoot complex workflows.

Skills

LangChain

RAG workflows

Python

Asynchronous programming

AWS cloud

LLMs

Tools

Docker

FastAPI

Uvicorn

Lambda

ECS

Datadog

ddtrace

Qdrant

Job description

Job Title: Python-Langchain Lead

Job Descriptions:

We are looking for a Python Lead with minimum 6 to 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.

Required Skills:

• Proficiency in LLM and RAG Workflows: experience with LangChain and vector databases, applying RAG techniques for intelligent data retrieval and generation.
• Python Proficiency Advanced Python skills, including experience with asynchronous programming.
• Proficient in AWS environment
• Understanding of MCP Servers