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Metro locations and mid-level experience raise competition, though niche GenAI skills moderately reduce applicant pool.
Generative AI and backend Python skills are widely transferable across industries.
Explicit 4–9 years and mandatory GenAI, LangChain, vector DB, Python, cloud make filters strict.
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Design, develop, and deploy Generative AI applications using Large Language Models (LLMs), LangChain, and LangGraph.
Build AI agents and intelligent workflows, integrating Retrieval-Augmented Generation (RAG) solutions with vector databases.
Develop scalable backend services and APIs in Python and optimize prompts to improve model accuracy and performance.
4 to 8 years of hands-on Python development experience.
Practical experience with Generative AI concepts, LLMs, LangChain, LangGraph, and prompt engineering.
Experience with AI Agents, RAG architecture, and vector databases like Pinecone, ChromaDB, Weaviate, or FAISS.
Location requirement: Bengaluru or Hyderabad.
Candidate has strong backend development skills with REST APIs, microservices, and cloud platforms (Azure, AWS, or GCP).
Experience in building scalable AI-driven enterprise solutions and optimizing GenAI model performance.
Comfortable working with structured and unstructured data and leveraging advanced AI orchestration tools (LangChain, LangGraph).