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About the Role
Mount Thor is hiring a software engineer to build the customer-facing control plane and managed services for our compute platform, enabling AI workloads on Apple hardware at datacenter scale.
Responsibilities
- Design, build, and operate managed Kubernetes and other customer-facing infrastructure services.
- Build control-plane services, Kubernetes operators, and controllers.
- Automate managed-service lifecycle, including cluster creation, version upgrades, configuration changes, and safe deletion.
- Coordinate with Fleet for the underlying capacity.
- Build APIs and tools for customers to deploy, manage, and monitor workloads.
- Integrate orchestration with compute, networking, storage, identity, and security systems.
- Improve service availability, isolation, performance, observability, and upgrade safety.
- Work directly with customers and Product to define and deliver new platform capabilities.
- Use coding agents throughout design, implementation, testing, debugging, and operations.
- Participate in on-call and own systems in production.
Requirements
- Built customer-facing infrastructure products or managed cloud services.
- Experience building distributed systems, control planes, operators, or controllers.
- Deep knowledge of Kubernetes internals and cluster lifecycle management.
- Strong programming skills in Go, Python, Rust, or a similar language.
- Strong knowledge of Linux, containers, networking, storage, and security.
- Experience building reliable multi-tenant services and public APIs.
- Led complex infrastructure work from design through production.
- Experience using coding agents to build production software.
Skills
- Go
- Python
- Rust
- Kubernetes
- Linux
- Containers
- Networking
- Storage
- Security
- Distributed systems
- Control planes
- Operators
- Controllers
- Multi-tenant services
- Public APIs
- Coding agents
Location
- Remote
Work Type
- Full-time
Experience Level
- Mid-level
- Senior
About the Company
- Mount Thor makes Apple hardware (macOS and Apple Silicon) available and performant at datacenter scale for AI workloads.
- We take consumer hardware and build the infrastructure platform around it to enable consumption as elastic compute exposed through developer-friendly interfaces.
- Our customers use us to develop computer-use model capabilities, deploy long-running agents, and accelerate agentic engineering.