Endpoint Engineer, IT
Thinking Machines Lab · San Francisco
CHECKED 13H AGO
Frontier labonsite$180k–$360k
At a glance
Highlights
- Operate endpoint fleet as distributed platform with testing and staged rollouts.
- Lead migration to new fleet platform with minimal disruption to employees.
- Design zero-touch provisioning that makes new devices secure and productive fast.
What they offer
- Generous health, dental, and vision benefits
- Unlimited PTO
- Paid parental leave
- Relocation support as needed
Ideal candidate
A production-minded endpoint engineer who loves automation and a secure, seamless employee experience. You thrive owning complex initiatives and partnering across IT and Security to move fast safely.
Requirements
- Python and shell scripting
- macOS internals, including launchd, configuration profiles, TCC, system extensions, Endpoint Security, FileVault, Secure Token, and bootstrap tokens
- Apple Business Manager, Automated Device Enrollment, and Apple's MDM and Declarative Device Management frameworks
- Modern Apple MDM platforms, particularly Iru, Fleet, Jamf, or equivalent
- Santa binary authorization and Rudolph synchronization infrastructure
- Fleet-scale querying and osquery
- Git, pull-request workflows, GitOps, and CI/CD for endpoint configuration
- Terraform and infrastructure as code
- Public-cloud fundamentals, including serverless infrastructure, containers, managed databases, and monitoring
- Device lifecycle automation, including zero-touch enrollment, patching, software distribution, and secure deprovisioning
- Endpoint security, Zero Trust, device trust, continuous posture evaluation, compliance, and automated remediation
- Proficiency in Swift or Go for building macOS endpoint tools, agents, or supporting services
- Experience using LLMs to automate operational work or interest in applying them to endpoint engineering
- visa sponsorship
- We sponsor visas
Lab profile
About Thinking Machines Lab
Builds frontier AI that extends human will and judgment through customizable models and interfaces.
What they build
- Inkling frontier models
- Tinker model customization
- Human-AI communication interfaces
Known for
- Frontier model training
- Post-training and reinforcement learning
- Evaluation infrastructure
- GPU supercomputing and reliability