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Tier-1 brand, mid-level role, and metro locations drive high applicant competition.
Specialized LLM, RAG, and agentic AI skills limit cross-industry transferability.
Explicit 1–6 year range plus mandatory LLM, RAG, and vector DB skills increase shortlisting strictness.
Develop and maintain AI applications using Python, focusing on Agentic AI, LLMs, and Retrieval Augmented Generation (RAG) architectures.
Design, build, and optimize AI agents, RAG pipelines, and workflows leveraging frameworks like LangChain, LangGraph, CrewAI, or AutoGen, integrating large language models from providers such as OpenAI and Azure OpenAI.
Create and deploy scalable AI solutions and APIs on cloud platforms (Azure, AWS, GCP), monitor and enhance AI model performance, and collaborate with business and tech teams to translate needs into AI-driven products.
1 to 6 years of experience in Python development with expertise in Agentic AI, LLMs, and RAG architectures.
Proficient with frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, and vector databases like Pinecone, ChromaDB, Weaviate, or FAISS.
Experience developing REST APIs using FastAPI, Flask, or Django and working knowledge of cloud AI services, preferably Azure OpenAI.
Work Experience Required: 1 to 6 years (JL3/JL4 level). Location: Bangalore or Pune.
Experienced developer able to architect end-to-end AI solutions involving multi-agent systems, prompt engineering, and AI workflow orchestration.
Strong familiarity with cloud platforms and AI service deployment, including scalable microservices and containerization technologies like Docker and Kubernetes.
Candidate with knowledge of enterprise AI governance, responsible AI practices, and who can effectively evaluate and optimize AI models for accuracy and performance.