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Job Description
Structured overview of role & requirementsAbout This Role
Develop and implement AI agent workflows and components using modern AI/ML and LLM frameworks for enterprise AI systems.
Build and enhance retrieval augmented generation (RAG) pipelines, vector database integrations, and document intelligence workflows for structured and unstructured data.
Support prompt engineering, AI evaluation routines, and integration with LLM APIs and open source AI models.
Minimum Requirements
Strong programming experience in Python with hands-on AI agent development.
Practical exposure to LLMs, vector databases, embedding models, prompt engineering, and AI application development.
Experience with AI/LLM frameworks like LangChain, LangGraph, AutoGen, CrewAI or equivalents.
Working knowledge of REST APIs, microservices, Git, unit testing, and SQL including structured data concepts.
Ideal Candidate Profile
Engineer comfortable building complex, production-ready AI agentic systems beyond isolated demos.
Experienced in working collaboratively across AI architects, data engineers, and platform engineers in a startup/foundation-stage setting.
Practically skilled in prompt engineering, RAG pipelines, vector DBs, and document intelligence within enterprise AI contexts.