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Tier-1 brand, metro location, and mid-level role increase applicant competition despite GenAI specialization.
Core GenAI, RAG, and LLM engineering skills are highly transferable across industries.
Explicit 4–7 years plus mandatory GenAI, RAG, vector DBs, and advanced Python create strict filtering.
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Design and implement autonomous agents using frameworks like LangChain, Crew.ai, SK, and Autogen.
Develop and optimize Retrieval Augmented Generation (RAG) systems and implement monitoring, evaluation, and safety frameworks for agent behavior.
Contribute to improvement of agent architecture, document best practices, and handle deployment involving advanced Python, asynchronous programming, API development, and vector databases.
4 to 7 years of relevant experience in GenAI and Agentic AI technologies.
Bachelor's or Master's in Engineering, MCA, or MBA.
Proficiency in advanced Python programming including async programming and API development.
Experience with LangChain, RAG systems, LLMs, vector databases, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Experienced with autonomous agent development and deployment in production environments using multiple LLM providers and frameworks.
Knowledgeable about AI agent safety, hallucination resolution, semantic search, and retrieval techniques.
Skilled in managing agent orchestration, workflow management, and container technologies like Docker and Kubernetes.