Software Engineer - Cloud Engineering at Kumo

Mountain View, California, United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

AI, Machine Learning, Cloud ComputingIndustries

Requirements

3–5 years of experience building or operating cloud-native infrastructure in production
Hands-on experience with at least one major cloud provider (AWS, Azure, or GCP) and (preferably) exposure to multi-cloud environments
Solid understanding of Kubernetes concepts and operational experience with production clusters
Proficiency with Infrastructure-as-Code tools (Terraform, Pulumi, or similar)
Experience with GitOps workflows and tools like Argo CD, Flux, or Argo Workflows
Familiarity with monitoring, logging, and tracing for distributed systems
Scripting or programming skills in Python, Go, or Bash
Strong problem-solving skills and a collaborative approach

Responsibilities

Deploy, operate, and maintain infrastructure across AWS, Azure, and GCP
Build and manage Kubernetes clusters (EKS, AKS, GKE) with a focus on performance, availability, and cost efficiency
Develop and maintain automation using Infrastructure-as-Code tools (Terraform, Pulumi, Crossplane)
Implement and enhance GitOps workflows using Argo CD or Flux
Set up and maintain observability systems (Prometheus, Grafana, OpenTelemetry) to monitor workloads and clusters
Collaborate with the team to design, test, and roll out improvements to scaling and reliability
Troubleshoot incidents and participate in on-call rotations to ensure platform uptime
Contribute to security best practices, including RBAC, tenant isolation, and cloud identity management

Skills

Kubernetes

AWS

Azure

GCP

EKS

AKS

GKE

Terraform

Pulumi

Crossplane

Argo CD

Flux

Prometheus

Grafana

OpenTelemetry

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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