Principal AI Architect

Hop

  • San Francisco, CA
  • 30+ days ago

    Highlights

    Deep expertise across: LLM training and fine-tuning, agentic system design, knowledge graph construction, large-scale data modeling. We work with 250+ enterprise clients — including 5 of the Fortune 10 — processing 1B+ job descriptions, 850M+ professional profiles, and signals from 100+ labor databases.

    Numbers & Facts

    LocationSan Francisco, CA

    Description

    Draup is a Series A-funded agentic AI company building the intelligence layer for how global enterprises make workforce and go-to-market decisions. We work with 250+ enterprise clients — including 5 of the Fortune 10 — processing 1B+ job descriptions, 850M+ professional profiles, and signals from 100+ labor databases.
    We are now building our Silicon Valley engineering team — a small, senior group focused on next-generation AI research and product.
    What you'll do
    • Define and own the architectural vision for next-generation AI systems: novel agent architectures, reasoning systems, and proprietary model development.
    • Prototype and evaluate breakthrough AI capabilities — predictive modeling, autonomous signal synthesis, multi-modal intelligence — that create defensible IP.
    • Set the technical foundations: data architecture, model serving, agent orchestration, and inference infrastructure for a multi-year product horizon.
    • Evaluate and adopt emerging AI paradigms (multi-agent reasoning, RLHF, retrieval-augmented fine-tuning) before they are mainstream.
    • Establish engineering standards, architecture review processes, and IP documentation practices for the team.
    What we require
    • BS/MS/PhD in Computer Science, AI/ML, or related field. PhD or equivalent research depth preferred.
    • 5+ years in AI/ML engineering with at least 2 years in a principal engineer or lead architect role.
    • Demonstrated history of building original AI systems that became products — not implementations of existing patterns.
    • Deep expertise across: LLM training and fine-tuning, agentic system design, knowledge graph construction, large-scale data modeling.
    • Comfort operating in greenfield conditions: high ambiguity, high ownership.
    • Patents, published research, or shipped products with clear proprietary differentiation are strong signals.
    • No visa sponsorship. Must be authorized to work in the US without current or future employer sponsorship.

    Similar Jobs