AI Engineer - Relational Foundation Models & Agentic Systems at Kumo

Mountain View, California, United States

Kumo Logo
Not SpecifiedCompensation
Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Artificial Intelligence, Machine Learning, Enterprise SoftwareIndustries

Requirements

  • 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
  • Preferred Qualifications
  • Experience as a Founding Engineer or early builder at a startup/innovation pod
  • Experience with LangChain, LangGraph, LlamaIndex, OpenAI/Anthropic

Responsibilities

  • 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)

Skills

AI/ML
LLMs
SQL
APIs
Full-Stack Development
Frontend
Backend
Data Engineering
Agentic Workflows
Relational Data
Workflow Orchestration

Kumo

Generates and deploys predictive models

About Kumo

Kumo.ai specializes in creating and implementing accurate predictive models for organizations that need reliable forecasts for critical operations. Their platform uses Graph Neural Networks to analyze raw relational data, which removes the need for manual data preparation and enhances prediction accuracy and efficiency. Unlike many competitors, Kumo.ai's platform streamlines the entire Machine Learning lifecycle, from data preparation to model deployment, while also optimizing costs by eliminating unnecessary infrastructure. The company aims to provide a quick return on investment for its clients, which range from small businesses to large enterprises, by offering flexible deployment options through Software as a Service (SaaS) and Private Cloud models. Kumo.ai is built by experienced professionals from top tech companies and has already gained the trust of leading organizations globally.

Mountain View, CaliforniaHeadquarters
2021Year Founded
$35.5MTotal Funding
SERIES_BCompany Stage
Fintech, AI & Machine LearningIndustries
51-200Employees

Benefits

Stock Options
Medical Insurance
Dental Insurance

Risks

Increased competition from Databricks' Marketplace may divert potential customers.
The rise of multimodal AI could overshadow Kumo's current offerings.
Rapid AI advancements by tech giants may set new industry standards Kumo must meet.

Differentiation

Kumo.AI uses Graph Neural Networks for predictive modeling, eliminating manual feature engineering.
The platform offers a SQL-like Predictive Querying Language for rapid AI model creation.
Kumo.AI integrates with Snowflake's Native App Framework, enhancing model performance and scalability.

Upsides

Kumo's $18M Series B funding will expand its platform and market reach.
Integration with Snowpark Container Services enhances deep learning capabilities within Snowflake Data Cloud.
Kumo's platform supports both SaaS and Private Cloud models, offering client flexibility.

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