Job Description: Cloud Infrastructure Engineer at Kumo

Position Overview

• Location Type: Remote
• Employment Type: Full Time
• Salary: Not specified

As a key member of the Cloud Infrastructure team at Kumo, you will play a vital role in architecting scalable systems for the Kumo AI platform, a leading choice for Big Data and AI workloads. You’ll collaborate with ML scientists, product engineers, and leaders to influence scaling ML technology, develop tools for speed, and craft full-stack experiences. This role offers the opportunity to dive into foundational work, managing model lifecycles, ML Ops, CI/CD, and deployment strategies.

Requirements

• Education: BS/MS in Computer Science or a related field (PhD preferred)
• Kubernetes Expertise: 5-7+ years of experience managing Kubernetes (e.g., EKS, GKE, AKS, or OpenSource) in large-scale production environments, with deep knowledge of Kubernetes internals, controllers, operators, networking, and connectivity.
• Cloud Infrastructure: 5-7+ years of experience building cloud-native infrastructure across AWS, Azure, and GCP.
• Platform Engineering: 5-7+ years of experience developing platform engineering services using tools like Traefik, Istio/Envoy, and Calico/Tigera.
• Software Development: 5-7+ years of experience writing production code in Python, Go, Rust, or similar languages.
• Infrastructure-as-Code: Hands-on experience with IaC tools such as Terraform, CloudFormation, Ansible, Chef, and Bash scripting.
• B2B SaaS & Distributed Systems: Experience in architecting large-scale distributed systems for B2B SaaS applications.
• Cloud Application Deployment: Strong background in productionizing cloud applications, including Docker and Kubernetes.

Responsibilities

• Build and extend components of the core Kumo Cloud Infrastructure and Kumo infrastructure.
• Define a culture of engineering excellence and operational efficiency, especially as it relates to development and productization.
• Build and automate CI/CD pipelines, release tooling to support continuous delivery, and true zero-downtime deployments across different cloud providers using the latest cloud-native technologies.
• Work on advanced tools developed for the world’s leading cloud-native machine learning engine that uses graph deep learning technology.
• Develop the infrastructure microservices for features such as usage tracking, diagnostics, monitoring, and alerting at the cloud scale.
• Lead automation efforts to streamline global deployment effort.
• Build the Kumo ML Ops platform, which will be able to data drift, track model versions, report on production model performance, alert the team of any anomalous model behavior, and run programmatic A/B tests on production models.

Application Instructions

• Not specified in the provided text.

Company Information

• Company: Kumo
• Team: Cloud Infrastructure
• Platform: Kubernetes-based, cloud-native Kumo AI platform