Product: Foundation models for relational/structured enterprise data (zero-shot predictions, natural-language querying)
Employees: ~125
Latest known funding: Series B $18M (Sep 2022), lead: Sequoia
Company Overview
Problem Domain
Predictive analytics and ML for relational/structured enterprise data
Founded
2021
Industry
Artificial intelligence / SaaS
Funding Track Record
Series B- 2022-09-27
$18,000,000
Series B announced with participation from A.Capital, SV Angel and multiple angel investors.
Investor Signal
“Sequoia Capital led Series B; participation from prominent angels and firms (A.Capital, SV Angel, Ron Conway, Michael Ovitz, Frank Slootman, Kevin Hartz, Clément Delangue, Michael Stoppelman).”
Founders
What we do
Join the Team
AI Engineer
On-SiteSan Francisco Bay Area, US
On-Site • San Francisco Bay Area, US
Who you are
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
AI Researcher
Part-timeHaifa
Part-time • Haifa
Mobile Developer
Full-timeNovi Sad, RS
Full-time • Novi Sad, RS
Data Scientist
ContractCambridge, GB
Contract • Cambridge, GB
Mobile Developer
Part-timeAustin, US
Part-time • Austin, US
Software Engineer
Full-timeMunich, DE
Full-time • Munich, DE
Software Engineer
Full-timeAustin, US
Full-time • Austin, US
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
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
Experience as a Founding Engineer or early builder at a startup/innovation pod
Experience with LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic APIs, and multi-agent coordination libraries
Track record building full-stack features (you can dip into frontend/backend/data/infra as needed)
Experience integrating agents with enterprise systems and APIs; designing foundation APIs for tools
Background in knowledge graphs, GNNs, causal inference, or structured reasoning with LLMs
MLOps and cloud (AWS/GCP), model/agent serving, prompt/runtime observability, and eval pipelines
Familiarity with guardrails, safety, and governance for enterprise AI
What the job involves
With the launch of our new Kumo Relational Foundation Model (RFM), we’ve seen unprecedented interest from builders who want to create on top of our platform
This is your chance to be part of that momentum
You’ll be building applications and agentic workflows, demoing them to customers, and making core product and engineering decisions that shape the growth of our RFM offering
This is an engineering role at its core, but you’ll also interface directly with customers, the broader builder community, and cross-functional engineering teams
We’re looking for someone who thrives in that hybrid space—shipping product, representing engineering externally, and helping shape the direction of Kumo RFM from the ground up
We’re hiring an AI/ML Engineer to design and build AI-powered, user-facing products on top of our RFM
Understand a user’s goal and autonomously propose workflows for analysis, prediction, and optimization.
Interact with enterprise systems and APIs, orchestrating tools and data
Produce interpretable outputs that are easy to trust in real-world decisions
Demo prototypes and apps to customers, iterating on feedback and incorporating real use cases
You’ll work across product surfaces (UI/API), agent orchestration, data/infra, and model integration, collaborating tightly with product, design, ML research, and customers
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