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PwC brand and Bangalore metro increase candidate density, but niche LLM/agent skills limit competition.
ML/AI agent engineering skills transfer across industries but require specific LLM and tool expertise.
Explicit 2–3 year requirement plus mandatory LLM, RAG, vector DB, and Python skills increases filter strictness.
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Design and implement autonomous agents using frameworks like LangChain, Crew.ai, SK, Autogen.
Develop and optimize Retrieval Augmented Generation (RAG) systems and large language model (LLM) applications focused on enhancing information retrieval and response accuracy.
Create and maintain evaluation frameworks, monitoring systems, documentation, and best practices around autonomous agent performance and safety.
2 to 3 years of work experience in relevant AI engineering roles.
Advanced Python programming skills including async programming and API development.
Experience with vector databases, embedding models, RAG pipeline implementation, and prompt engineering for LLM optimization.
Educational qualifications: Bachelor of Technology, MBA, or equivalent higher degrees (ME, M.Tech, MCA).
Hands-on experience building and deploying autonomous agents with LangChain and similar frameworks.
Strong understanding and application of safety principles and techniques to resolve hallucinations in AI-generated outcomes.
Experience working with modern software development practices including Git, CI/CD pipelines, and testing in AI/ML development environments.