Back
Mid-level GenAI role in metro cities at a known IT services brand yields moderate applicant density.
GenAI engineering skills are transferable across industries but require specific LLM, LangChain and vector DB expertise.
Explicit 4–9 years plus mandatory GenAI, LangChain, vector DB and Python backend requirements create strict filters.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design, develop, and deploy Generative AI applications using Large Language Models (LLMs) with Python.
Build intelligent workflows and AI agents leveraging LangChain, LangGraph, and prompt engineering techniques.
Implement and optimize Retrieval-Augmented Generation (RAG) solutions integrating vector databases and LLM platforms in enterprise-grade backend services.
4 to 9 years of experience with 4 to 8 years in Python development.
Strong hands-on expertise in Generative AI concepts including LLMs, LangChain, LangGraph, and prompt engineering.
Experience with vector databases (e.g., Pinecone, ChromaDB, Weaviate, FAISS) and backend development using REST APIs and microservices.
Location requirement: Bengaluru or Hyderabad; Work type: Full-Time Employment.
Experienced Python developer deeply familiar with designing scalable AI applications using modern Generative AI frameworks and tools.
Proficient in configuring, optimizing, and integrating various LLM platforms and AI workflows in enterprise contexts.
Comfortable working with cloud platforms (Azure, AWS, or GCP) and DevOps tools like Git and CI/CD pipelines to maintain robust AI services.