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Tier-1 employer, metro location, and mid-level role make applicant competition high despite specialized GenAI skills.
Role requires specialized GenAI and agentic AI expertise, limiting cross-industry transferability.
Explicit 4–7 years plus mandatory LangChain, RAG, LLM, async Python and vector DBs increases filter strictness to high.
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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 for better information retrieval and response accuracy.
Establish evaluation frameworks and monitoring systems to test agent performance, safety, and behavior, while documenting best practices.
4 to 7 years of work experience in relevant technologies.
Bachelor's degree in Engineering or MBA; BE/BTech/MCA/MTech/MBA specified.
Advanced Python programming skills, 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).
Proven experience in building and deploying autonomous agents with LangChain and similar AI frameworks.
Strong understanding of large language models (LLMs), safety principles, hallucination resolution, and agent capability improvements.
Familiarity with multiple LLM providers, container technologies, NLP techniques, and agent orchestration tools to enhance AI workflows and safety.