Back
Tier-1 brand, metro location, and a mid-level experience band increase qualified applicant density.
Requires specialized GenAI, LLM and RAG expertise, somewhat transferable but still domain-specific.
Explicit 4–7 years plus mandatory GenAI, Python, RAG, and vector-database skills enforce strict shortlisting.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Design and implement autonomous AI agents and optimize Retrieval Augmented Generation (RAG) systems to enhance information retrieval and response accuracy.
Develop evaluation frameworks, monitoring, and logging systems to ensure agent performance, safety, and reliability.
Contribute to improving agent architectures and develop documentation and best practices for agent development.
4 to 7 years of work experience in relevant AI or software development roles.
Bachelor's degree in Engineering (BE/BTech) or Master's in Business Administration (MBA) mandatory; MCA/MTech also accepted.
Advanced Python programming skills including async programming and API development mandatory.
Experience with vector databases, embedding models, RAG pipelines, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Demonstrated expertise in building and deploying autonomous agents using frameworks like LangChain and managing large language model (LLM) APIs.
Strong understanding of AI safety principles, hallucination resolution, and agent alignment in generative AI systems.
Experience with multiple LLM providers, agent orchestration tools, containerization (Docker/Kubernetes), and semantic search methodologies.