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Tier-1 employer, mid-level experience band and metro location drive high competition despite niche GenAI skills.
Highly specialized GenAI, LangChain, RAG and LLM expertise limits cross-domain transfer without relevant AI experience.
Explicit 4–7 years plus mandatory GenAI, LangChain, RAG, vector DB and advanced Python skills raises strictness.
Design and implement autonomous AI agents using frameworks like LangChain, optimizing Retrieval Augmented Generation (RAG) systems for improved information retrieval and response quality.
Develop and maintain evaluation, monitoring, and logging systems for agent behavior ensuring performance, safety, and reduction of hallucinations in AI outcomes.
Produce documentation and contribute to agent architecture improvement, utilizing advanced Python programming, async programming, and API development.
4 to 7 years of relevant work experience in AI or related fields.
Educational qualification required: BE/BTech/MCA/MTech/MBA.
Strong skills in advanced Python programming, async programming, API development, and experience with vector databases and embedding models.
Proficiency in implementing RAG pipelines, prompt engineering, LLM optimization, and modern software development practices (Git, CI/CD, testing).
Experienced in building and deploying autonomous AI agents and familiar with multiple generative AI frameworks and providers (e.g., OpenAI, Anthropic).
Capable of developing and optimizing AI systems with a focus on safety principles, agent alignment, and handling hallucinations.
Comfortable working in a data and analytics engineering environment using modern tools, including container technologies, and knowledge of NLP, semantic search, and information retrieval.