Refine the product flow and user interface while developing the frontend.
Identify key technical requirements to optimize workflows for indirect spend categorization with RAG+LLMs, unique part identification extraction, agentic AI-driven benchmarking strategies, and agentic AI negotiation automation.
Implement LLM, RAG, and agentic AI pipelines to process and analyze large-scale procurement data, generate actionable insights, and power intelligent spend recommendations.
Train LLMs and implement agentic AI tailored to procurement, creating intelligent agents that find online benchmarks, clean and triangulate dirty data to find critical part information, find contact information from suppliers online, communicate with suppliers, reduce costs, and drive measurable value for enterprises.

Requirements

5+ years of full-stack development with a strong grasp of product strategy.
Proven work on LLM projects, ideally including agentic workflows, with ability to discuss specific use cases, architectures and technical challenges.
Tech Stack: Next.js (TypeScript), Supabase (PostgreSQL), Node.js, Langsmith
Experience building 0 –> 1 in a startup, earlier stage the better.
Demonstrated proficiency in writing clean, reliable code with effective testing (unit / integration).
Ability to walk us through a technical project you have led or significantly contributed to, in detail.
Comfortable with ambiguity and evolving project requirements, with a track record of iterating quickly.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

full-stack developmentproduct strategyLLM projectsagentic workflowsclean codeunit testingintegration testingNext.jsTypeScriptNode.js

Soft Skills

communicationproblem-solvingadaptabilityleadershipcollaborationcritical thinkingproject managementattention to detailcreativitytime management