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Tier-1 employer, mid-level experience band, and Bangalore metro increase candidate competition despite niche GenAI specialization.
Specialized GenAI and agent engineering skills are transferable across sectors but require ML/LLM-specific experience.
Explicit 4–7 years plus mandatory GenAI, RAG, vector DB and advanced Python requirements enforce strict technical filters.
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Design and implement autonomous AI agents using frameworks like LangChain, Crew.ai, SK, and Autogen.
Develop and optimize Retrieval Augmented Generation (RAG) systems to enhance information retrieval and response generation.
Create evaluation, monitoring, and documentation frameworks to ensure agent performance, safety, and continuous improvement.
4 to 7 years of relevant work experience.
Strong expertise in advanced Python programming including async and API development.
Proficiency with LangChain framework, RAG systems, large language models (LLMs) and their APIs.
Educational qualification: BE/B.Tech, MCA, M.Tech, or MBA.
Experienced in building and deploying autonomous AI agents with proven hands-on skills in LangChain and RAG pipelines.
Knowledgeable in vector databases, embedding models, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Familiarity with multiple LLM providers and concepts related to agent safety, alignment, and information retrieval is preferred.