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Mid-level GenAI role, metro location and broad LLM skills drive high applicant competition.
Generative AI and LLM skills are transferable across industries but require specialized agent and RAG expertise.
Explicit 3–5 years plus mandatory LLM, RAG, and tooling experience implies high shortlisting strictness.
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Design, develop, and deploy Machine Learning and Generative AI solutions including Retrieval-Augmented Generation (RAG) pipelines using vector databases.
Develop and integrate AI agents with enterprise APIs, tools, and databases using frameworks like LangChain, LangGraph, or CrewAI.
Optimize LLM applications in terms of accuracy, latency, and cost while maintaining and improving model and agent performance.
3-5 years of work experience in AI/ML or related roles.
Strong proficiency in Python and core ML fundamentals including NLP and Generative AI technologies.
Experience with Agentic AI frameworks such as LangChain and LangGraph, and building AI agents with tool-calling workflows.
Knowledge of vector databases, LLM APIs (OpenAI, Anthropic, Azure OpenAI, etc.), cloud platforms (AWS, Azure, GCP), and containerized deployments.
Pragmatic engineer with hands-on experience building and deploying production-grade AI or LLM-powered applications.
Familiar with multi-agent systems, workflow orchestration, and advanced LLM fine-tuning techniques.
Experienced in collaborating cross-functionally with product managers and software engineers to deliver AI-driven solutions in enterprise environments.