Founding Agentic AI Product Engineer
NegotiateAI7 months ago
San Jose, CA, USASenior
Responsibilities
- Build end-to-end AI agents for taxonomy cleanup, chemical and part classification, CAS lookup, entity resolution, attribute extraction, supplier benchmarking, supplier outreach, negotiation preparation, purchasing automation, and exception handling.
- Architect modular agentic pipelines using LLMs, Retrieval Augmented Generation, embeddings, and deterministic logic.
- Design cohesive product flows that connect data cleaning, benchmarking, agent actions, and user decision-making.
- Design the intelligence layer and core data model, including taxonomies, schemas, semantic relationships, and supplier or part hierarchies.
- Implement pipelines for synonym resolution, unit-of-measure normalization, multilingual parsing, attribute extraction, and CAS-level matching.
- Build evaluation, monitoring, and guardrail systems so agents are accurate, safe, auditable, and enterprise-ready.
- Support rigorous data handling through anonymization, tokenization, SOC II principles, and GDPR alignment.
- Collaborate with the founder and engineering team to turn customer problems into scalable product patterns and reusable AI components.
- Influence the long-term product direction toward a broader industrial operations AI layer.
Requirements
- 6–8+ years of experience in AI engineering, ML systems, or technical product roles.
- Demonstrated experience building agentic workflows or multi-step AI systems end to end.
- Production-grade coding ability in Node, Python, and TypeScript.
- Experience architecting data models, pipelines, services, and agent frameworks.
- Experience integrating LLMs, Retrieval Augmented Generation, embeddings, and semantic search.
- Strong product judgment and ability to design clean, scalable user flows.
- Experience shipping real products quickly in a 0-to-1 startup environment from Seed to Series B.
- Ability to build evaluation, observability, monitoring, guardrail, or reinforcement-loop systems for AI agents is preferred.
- Experience with industrial or manufacturing data, ERP systems, supply chain, chemicals, or procurement is preferred but not required.
- Early experience at a large technology company, prior founder or founding engineer experience, and consumer-grade or polished enterprise UX experience are preferred.
- Applicants should provide 1–2 examples of agentic systems or AI-driven workflows built end to end.
Tech Stack
Categories
AI ApplicationsProduct Engineering
About NegotiateAI
Backed by Menlo Ventures, NegotiateAI captures millions in savings across your manufacturing procurement spend. NegotiateAI is your go-to procurement platform for analyzing, benchmarking, and automatically negotiating indirect spend.