Full-Time
Senior Software Engineer
UpBound
51-200 employees
Cloud-based managed control planes with auto-scaling
No salary listed
La Ronge, SK, Canada
Remote
 Software Engineering (1) |
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- Experience operating production cloud services at scale: monitoring, alerting, incident response, post-mortems, and continuous improvement of service reliability.
- Strong debugging skills across distributed systems, including experience with observability tools (Prometheus, Grafana, OpenTelemetry, distributed tracing) and techniques for diagnosing issues in production environments.
- Experience building and operating controllers that interact with the Kubernetes API server, including troubleshooting reconciliation loops, managing API rate limits, and optimizing controller performance.
- Comfortable working directly with customers to understand, reproduce, and resolve complex technical issues in their environments.
- Take responsibility and ownership for solving problems even if they are outside your lane, especially during incidents affecting customer workloads.
- Demonstrate excellence in your work, constantly trying to improve your skills and the operational posture of the systems you build.
- Have empathy for customers and keep them in mind as you build solutions, understanding that reliability and debuggability are features.
- Realize the importance of clear communication and effective collaboration to work as a team, deliver great results, and support customers through technical challenges.
- Help create a safe environment where everyone can contribute, learn from failures, share on-call knowledge, and help each other grow as operators and engineers.
- Actively build and operate Upbound Spaces in production, troubleshooting and resolving issues across multi-tenant SaaS environments, as well as contributing to Upbound's open-source projects, including Crossplane.
- Take ownership of building features in high demand by Upbound's customers and deliver new functionality that will delight and amaze our users.
- Investigate and debug complex issues in customer environments, including multi-control plane scenarios, resource reconciliation problems, and performance bottlenecks.
- Communicate through thoughtful and thorough design documents for new initiatives and detailed post-incident reviews that drive system improvements.
- Support the full project lifecycle for highly scalable and reliable services running in a cloud environment – discovery, analysis, architecture, design, review, documentation, building, migration, automation, deployment, production-readiness, and ongoing operational support.
- Write and maintain Go code that interfaces with the Kubernetes API, such as operators, controllers, add-ons, etc., with a focus on observability, debuggability, and operational excellence.
- Deploy, manage, and troubleshoot our Kubernetes services in production, using metrics, logs, and traces to identify and resolve issues quickly.
- Build and maintain operational tooling for debugging customer environments, analyzing control plane health, and automating incident response.
- Author documentation, user guides, runbooks, and blog posts to support and promote new features that you release.
- Support the software release cycle for Spaces self-hosted distributions, including diagnosing issues in customer-managed deployments.
- Participate in on-call rotation to support Upbound Cloud, responding to incidents and driving them to resolution.
Upbound.io provides cloud-based tools to manage and govern cloud infrastructure, including managed control planes that let platform teams scale resources and centrally control across cloud providers and cloud-native tools. It auto-scales control planes to support platforms with large CRD workloads and offers Upbound Spaces to deploy managed control planes in a customer’s own environment for data privacy. The service is sold on a subscription basis. It differentiates itself with centralized cross-cloud control, automatic scaling for large CRD workloads, and on-premises or private deployments to meet privacy needs, with the goal of helping organizations manage cloud infrastructure more efficiently and accelerate platform innovation.
Company Size
51-200
Company Stage
Series B
Total Funding
$69M
Headquarters
Seattle, Washington
Founded
2017
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Simplify's Take
What believers are saying
- Upbound V3 launched August 2026 with air-gapped deployment and disaster recovery.
- Modelplane launched June 2026, opening a new AI infrastructure category.
- Upbound claims 1,000-plus production customers and 100-country reach, supporting sales momentum.
What critics are saying
- Terraform, Pulumi, ACK, and Config Connector commoditize Crossplane-style infrastructure control.
- Upbound depends heavily on Crossplane; developer abandonment would weaken every product line.
- Platform teams can skip Upbound and adopt vendor-native or open-source alternatives immediately.
What makes UpBound unique
- Crossplane reached CNCF Graduation in 2025 and 100 million downloads.
- Upbound V3 unifies fleet-wide API, governance, and visibility across control planes.
- Modelplane extends Crossplane into AI inference orchestration, targeting regulated and sovereign deployments.
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Benefits
Equity
Health care benefits
401k plan
Work from anywhere
Flexible hours & PTO
Home office stipend
Growth & Insights and Company News
6 month growth
↓ -1%1 year growth
↓ -3%2 year growth
↓ -5%Upbound launches platform to unify cloud and AI infrastructure operations. New release gives platform teams one view, one API and one governance model across their entire fleet of control planes, built for both engineers and AI agents. Upbound, the company behind Crossplane, today announced Upbound V3, a major expansion of its infrastructure platform designed to give enterprises a unified way to operate and govern cloud and AI infrastructure across clouds, data centers and teams. Enterprise infrastructure is increasingly fragmented across business units, clouds, on-premises environments and the tools individual teams have adopted. Each control plane manages its own part of that infrastructure, but organizations often lack a unified way to see what is running, understand its state and consistently govern who or what can make changes. That challenge is becoming more urgent as AI agents begin operating infrastructure alongside engineers. Human operators can bridge gaps between Git, cloud consoles, pipelines and internal documentation using experience and judgment. AI agents need infrastructure state, permissions and governance available programmatically and consistently. Upbound V3 addresses that problem by bringing an organization's control planes together into a single platform, providing fleet-wide visibility, a unified API and centralized governance. Engineers, automation and AI agents can operate through the same system and under the same policies, regardless of where individual control planes are deployed. "AI is changing not only how software gets built, but who operates the infrastructure underneath it," said Bassam Tabbara, CEO and Founder of Upbound. "Platform teams need a way to give engineers and AI agents access to infrastructure without creating another layer of fragmented tooling or sacrificing governance. Upbound V3 gives them one platform for operating their entire control plane fleet, whether the work is being done by a person, a pipeline or an agent." "AI is changing the demands placed on enterprise infrastructure and the teams responsible for operating and managing it," said Matthew Flug, Research Manager, Intelligent Application Modernization and Deployment Platforms, IDC. "As organizations introduce AI agents into infrastructure operations, having consistent visibility, access controls and governance across environments is becoming increasingly important." Upbound's approach builds on Crossplane, the open source control plane framework created by Upbound. Crossplane became a CNCF Graduated project in 2025 and has surpassed 100 million downloads, with production adoption at more than 1,000 organizations. Aug 20, 2026 Prev Next 1 of 43,508 One Platform Across Every Control Plane Upbound V3 introduces a common way for people, software and AI agents to interact with infrastructure while maintaining the same underlying view and governance model. * Hub provides a unified API across an organization's control plane fleet. It indexes resources across connected control planes so platform teams, developer portals, compliance systems and AI agents can query what exists and understand its state without connecting to each control plane individually. * Console provides a unified web interface for interacting with Upbound products and control planes, giving human operators a single place to view and manage infrastructure. One Governed Fleet for Humans and AI Agents Upbound V3 introduces a unified identity and access model across the control plane fleet, with single sign-on, fleet-wide role-based permissions and centrally managed credentials. The same governance applies whether an infrastructure request comes from an engineer or an AI agent. AI systems can be authenticated, scoped to specific permissions and audited, with policy enforced where infrastructure changes occur. This allows organizations to introduce AI agents without creating a separate governance model. Fleet-Wide Infrastructure Insights Upbound Insights, new in V3, gives platform teams a live view across their infrastructure estate, including resources managed by Upbound Control Plane and the Kubernetes clusters beneath them. Teams can search and investigate infrastructure from a single view rather than connecting to individual control planes or scripting across environments. Upbound Control Plane remains the company's core product for operating and governing control planes. V3 adds cross-region disaster recovery and scheduled disaster recovery exercises per control plane. Secure Software Supply Chain Marketplace now provides per-version CVE summaries and downloadable SBOMs before installation, plus a private registry for internal packages. Official and partner images are signed and delivered as SLSA Level 2 images with backported security patches and defined support windows. Cloud, On Premises and Air-Gapped V3 extends self-hosting across the platform, including Console, and supports fully air-gapped deployments. Organizations can use the same capabilities and governance across cloud, on-premises and isolated environments. Together, these capabilities advance Upbound's vision of one infrastructure platform with consistent visibility and governance for engineers, automation and AI agents.
Upbound has launched Upbound V3, a platform that unifies cloud and AI infrastructure operations across enterprise environments. The San Mateo-based company, which created the open source Crossplane framework, designed the platform to give organisations fleet-wide visibility, a unified API, and centralised governance across control planes. The release addresses growing infrastructure fragmentation as enterprises operate across multiple clouds, data centres, and business units. Upbound V3 enables both engineers and AI agents to work through a single system under consistent policies. "Platform teams need a way to give engineers and AI agents access to infrastructure without creating another layer of fragmented tooling or sacrificing governance," said Bassam Tabbara, CEO and founder of Upbound. Crossplane became a CNCF Graduated project in 2025 and has surpassed 100 million downloads, with production adoption at over 1,000 organisations.
Upbound launches Modelplane: the open source control plane for AI inference. June 23, 2026 Press play to listen to this content SAN FRANCISCO, June 23, 2026 - Upbound, the company behind Crossplane, today released Modelplane, an open source control plane for AI inference fleets. Modelplane is designed to do for AI inference what Crossplane did for cloud infrastructure: provide a vendor-neutral, open source orchestration layer that unifies fragmented, heterogeneous environments under a single system of control. AI inference is undergoing the same transformation that cloud infrastructure experienced a decade ago. Open-weight models have expanded who runs AI - neoclouds, regulated enterprises, and AI-native companies now operate their own GPU fleets across multiple clouds and on-premise environments. Cluster-level tooling has matured rapidly. But no open source system manages these fleets as a whole: placing model deployments across available capacity, autoscaling replicas based on load, provisioning and managing the underlying infrastructure, caching and distributing model weights, and routing inference through a unified gateway. Modelplane fills that gap. Built on Crossplane, a CNCF Graduated project that serves as the foundation for internal platforms at thousands of organizations, including Apple, Nike, JPMC NASA Science Cloud, Elastic, Grafana, SAP, IBM, and Akamai, Modelplane inherits a mature infrastructure orchestration framework and extends it to the inference layer. It sits above existing serving engines, schedulers, and gateways composing them into a unified fleet-wide system. Bassam Tabbara, Upbound CEO and founder, commented: "Open-weight models are changing who runs AI. Over the next few years, many more organizations will run inference on infrastructure they own and control, and they'll all encounter the same problem: inference doesn't stay on one cluster. Kubernetes became the standard control plane for compute. Crossplane extended that model to cloud infrastructure. AI inference needs the same layer. We've spent years watching operators build fleet-level inference platforms on top of Kubernetes and Crossplane. Modelplane is our contribution back to the community: an open control plane for AI inference, shaped by those real-world patterns and built in the open from day one." Modelplane is available today as an early open source developer release under the Apache 2.0 license. Upbound intends to develop the project in the open with the community as it evolves toward production readiness and plans to donate it to an open source foundation later this year. A control plane that sits above the ecosystem should belong to the ecosystem. What Modelplane Does Modelplane is not another inference engine, scheduler, or gateway. It operates at the fleet level, above the cluster, and provides: * Fleet-wide model scheduling: decides where models run across available and compatible GPU capacity, clouds, and regions * Autoscaling: scales model replicas based on load and cost optimization targets * Infrastructure lifecycle management: provisions and manages clusters, nodes, and accelerators * Weight caching and distribution: efficiently propagates model weights across the fleet * Unified inference gateway: routes requests with fallback to managed providers; enforces cost, compliance, and sovereignty policies Built for Organizations That Run Their Own Inference Modelplane is built for organizations that operate their own inference rather than rely on a managed API provider. It is designed to be neutral across models, infrastructure providers, accelerators, clouds, and serving stacks. Three segments define the target market: * Neoclouds and AI factories - organizations building managed inference services on their own hardware who need a fleet control plane without building it from scratch * Regulated and sovereign enterprises - organizations where inference must run inside infrastructure they control, under their own governance, due to sovereignty, security, or compliance requirements * AI-native companies - organizations with significant inference spend that are moving to open-weight models and need control over cost, performance, and model differentiation Availability Modelplane is available today at https://github.com/modelplaneai/modelplane under the Apache 2.0 license. Documentation and getting-started guides are available at docs.modelplane.ai. Organizations interested in design partnership or commercial evaluation should contact Upbound at https://www.upbound.io/contact-us. About Upbound Upbound is pioneering infrastructure platforms for the agentic AI era, serving Fortune 500 companies and platform engineers across more than 100 countries. The company empowers infrastructure and platform teams with intelligent control planes, based on Kubernetes and Crossplane, that provision, operate, and adapt so platforms are ready for both humans and AI agents. Upbound is the creator and primary maintainer of Crossplane, the popular open-source framework for building cloud-native control planes, with over 100 million downloads and adoption by more than 1,000 organizations in production worldwide. Founded in 2017 and headquartered in San Mateo, CA, a Series B startup backed by GV (formerly Google Ventures), Altimeter Capital, and Intel Capital, Upbound has raised $69M to date. For more information, visit www.upbound.io.
Upbound has launched Modelplane, an open source control plane for AI inference fleets. Built on Crossplane, the system provides fleet-wide orchestration for organisations running their own GPU infrastructure across multiple clouds and on-premise environments. Modelplane handles model scheduling across available GPU capacity, autoscaling based on load, infrastructure lifecycle management, weight caching and distribution, and unified inference routing. The platform targets neoclouds, regulated enterprises and AI-native companies operating their own inference rather than using managed API providers. Available under Apache 2.0 licence, Modelplane is released as an early developer version. Upbound, a Series B startup that has raised $69 million, plans to donate the project to an open source foundation later this year. The company is backed by GV, Altimeter Capital and Intel Capital.
Upbound, developer of AI-driven software designed for b2b sales development, raised $100,000 of venture funding.