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Tier-1 employer and metro mid-level role, but specialized GenAI agent skills narrow the pool.
Specialized GenAI agent engineering skills transferable across industries but require strong ML/AI expertise.
Explicit 4–7 years plus mandatory GenAI, RAG, vector DBs, async Python and LLM skills.
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Design and implement autonomous agents using frameworks like LangChain, Crew.ai, and Autogen, focusing on functionality and safety.
Develop and optimize Retrieval Augmented Generation (RAG) systems and evaluation frameworks to improve information retrieval and agent performance.
Implement monitoring, logging, documentation, and contribute to enhancement of agent architectures and capabilities.
4 to 7 years of relevant experience in AI, autonomous agents, or related fields.
Bachelor's or Master's degree in Engineering, Computer Applications, or MBA (BE/BTech/MCA/MTech/MBA).
Strong proficiency in advanced Python programming including async programming and API development.
Experience with vector databases, embedding models, RAG pipelines, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Experienced in building and deploying autonomous agents with LangChain framework and handling Large Language Models (LLMs) with their APIs.
Demonstrates strong understanding of agent safety, hallucination resolution, and agent alignment principles.
Familiarity with multiple LLM providers (e.g., OpenAI, Anthropic), agent orchestration tools, NLP, container technologies (Docker, Kubernetes), and semantic search concepts.