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Tier-1 brand, metro location, and mid-level GenAI skills make applicant competition high.
GenAI engineering skills are transferable across industries but require specific LLM and RAG experience, so medium sensitivity.
Multiple mandatory technical skills (Python async, RAG, vector DBs, LLMs) and explicit years requirement create high strictness.
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Design and implement autonomous agents and develop Retrieval Augmented Generation (RAG) systems to improve information retrieval and response generation.
Create evaluation frameworks for agent performance, implement monitoring/logging for agent behavior, and contribute to improving agent architectures and capabilities.
Apply advanced Python programming, manage vector databases and embedding models, and utilize LangChain and other relevant frameworks in developing AI-driven automation solutions.
1 to 3+ years of relevant experience in AI/automation engineering.
Bachelor's degree required: BE/BTech/MCA/MTech/MBA in relevant fields.
Mandatory skills: Advanced Python programming (including async and API development), experience with vector databases, embedding models, RAG pipelines, prompt engineering, and LLM optimization.
Work experience required: 1+ years. Notice period: Not explicitly mentioned in the JD.
Hands-on experience building and deploying autonomous agents using frameworks like LangChain, Crew.ai, SK, Autogen, etc.
Strong understanding of Safety principles in AI, resolving hallucinations in LLM outputs, and knowledge of agent alignment and safety considerations.
Familiarity with modern software development practices (Git, CI/CD, testing), multiple LLM providers, NLP techniques, container technologies, and agent orchestration tools.