Back
Tier-1 employer, mid-level experience, and Bangalore metro increase applicant density despite technical niche.
GenAI and agent engineering skills are transferable across industries but need specific LLM and RAG expertise.
Explicit 4–7 years and mandatory GenAI, LLM, RAG, Python, and vector-db skills enforce strict filters.
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 using frameworks like LangChain and Crew.ai, focusing on agent architecture, evaluation, and safety.
Develop and optimize Retrieval Augmented Generation (RAG) systems and implement monitoring/logging for agent behavior.
Develop documentation, best practices, and actively contribute to improving agent capabilities and architecture.
4 to 7 years of relevant work experience in AI/automation engineering.
Proficiency in advanced Python programming including async programming and API development.
Experience with LangChain framework, RAG systems, LLM APIs, vector databases, embedding models, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Education: Bachelor's or Master's in Engineering, MCA, M.Tech, or MBA.
Experienced in building and deploying autonomous AI agents with practical knowledge of safety and hallucination mitigation in outputs.
Comfortable working with multiple LLM providers (e.g., OpenAI, Anthropic) and agent orchestration tools.
Familiar with NLP techniques, container technologies like Docker/Kubernetes, semantic search, and agent alignment/safety considerations.