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High due to Tier-1 brand, metro location, mid-level ML role, and strong candidate demand for GenAI skills.
High because specialized GenAI, RAG, agent development, and LLM expertise limit easy cross-industry transfer.
High because explicit years plus many mandatory technical skills (Python async, RAG, vector DBs, LLM expertise).
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Design and implement autonomous agents using LangChain, Crew.ai, Autogen, and similar frameworks.
Develop and optimize Retrieval Augmented Generation (RAG) systems for enhanced information retrieval and response generation.
Create evaluation frameworks and monitoring systems for agent performance, behavior, and safety.
2 to 3+ years of relevant work experience.
Bachelor’s degree in Computer Science, Computer Engineering, Information Systems, or related fields; MBA also mentioned.
Advanced Python programming skills with async programming and API development expertise.
Experience with vector databases, embedding models, RAG pipeline implementation, prompt engineering, and modern software development practices (Git, CI/CD, testing).
Experienced in building and deploying autonomous agents using LangChain and familiar with large language models (LLMs) and their APIs.
Strong understanding of agent architecture improvement, safety principles, and resolving hallucinations in AI outputs.
Comfortable with development frameworks and tools, including multiple LLM providers, agent orchestration, NLP techniques, container technologies, and semantic search concepts.