Kumo.AI

AI Engineer, Relational Foundation Models and Agentic Systems

Kumo.AI

full-time

Posted on:

Origin:  • 🇺🇸 United States • California

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Salary

💰 $125,000 - $175,000 per year

Job Level

Junior

Tech Stack

AWSCloudGoogle Cloud PlatformNumpyPandasPythonPyTorchSQLTensorflow

About the role

  • Design, implement, and deploy AI agents that assist data scientists on relational/SQL data and recommend next-best actions.
  • Build user-centric APIs and product surfaces (web/UI or programmatic) that make agentic workflows feel seamless and reliable.
  • Integrate Kumo’s Relational Foundation Model with enterprise data systems; contribute to tooling, retrieval, and guardrails.
  • Develop adaptive, multi-step workflows (LLM orchestration, tool use, feedback loops) that continuously refine outputs.
  • Ensure interpretability and evaluation: traceability of steps, confidence scoring, and human-in-the-loop review.
  • Collaborate with PM/design/ML research to turn ambiguous problems into shippable product; instrument, measure, iterate.
  • Demo your work to customers and community, serving as a visible builder and advocate for Kumo RFM.
  • Optimize for latency, cost, and reliability in production environments (serving, caching, tracing, observability).

Requirements

  • Comfortable in an innovation pod or startup environment, moving quickly from idea → prototype → ship.
  • A tinkerer at heart who’s built full‑stack apps (frontend, backend, data) and lately has been hands‑on with the LLM tooling ecosystem.
  • Collaborative and easy to work with—you know how to partner with PMs/design/ML, bounce ideas, and get things done together.
  • Bonus: experience as a Founding Engineer or early builder who has shaped product direction from the ground up.
  • Minimum Qualifications:
  • 1+ years in ML/AI product development or software engineering (startup or fast-paced product teams).
  • Hands-on with embeddings, vector databases, and RAG; practical experience evaluating retrieval quality.
  • Strong background in deep learning/transformers/foundation models and LLM orchestration (tool use, planning, memory).
  • Experience with relational data & SQL; structured reasoning on business datasets.
  • Proficiency in Python and familiarity with data wrangling (Pandas, NumPy).
  • Strong product sense and collaboration skills—comfortable working with PMs/design and iterating with users.