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Designs, builds, and operates secure, scalable platform infrastructure for industrial automation applications. Responsibilities include infrastructure provisioning, CI/CD, GitOps, Kubernetes, cloud and on-prem systems, observability, security, incident readiness, documentation, and on-call support. The role partners with R&D and Operations to improve developer tooling and maintain software-defined automation platforms.
RETHINK MANUFACTURING
The only way to ignite change is to build the best team. At Bright Machines, we’re innovators and experts in our craft who have joined together to manufacture the AI and data center infrastructure at the edge. We believe unifying software, intelligent automation, and data is the answer to delivering quality and flexibility at scale. We deliver products to meet the demands of today while continuously investing in our Bright Factory model to take advantage of what comes next.
Working with us means you’ll have the opportunity to make lasting, impactful changes for our company and our customers. If you’re ready to apply your exceptional skills to a brighter way of manufacturing AI infrastructure, we’d love to speak with you.
ABOUT THE ROLE
At Bright Machines, we are transforming the future of manufacturing with intelligent, software-driven automation. Our applications help designers create products that are optimized for automated assembly, making factories more efficient and effective.
As a Platform Engineer, you will design, build, and operate scalable, secure infrastructure while driving monitoring, alerting, CI/CD pipelines, and developer experience tooling that accelerate development and automation of complex, mission-critical industrial manufacturing applications. Working closely with the Platform Engineering team, R&D, and Operations, you will play a key role in shaping and maintaining the core platform that powers our automation solutions.
Our technology stack includes on-prem compute and networking, AWS and Azure cloud, Terraform (IaC), ArgoCD, Kubernetes (self-hosted and managed), GitLab and observability tools such as Grafana, Prometheus, and OpenTelemetry.
This is an exciting opportunity to work with R&D teams designing & building software-defined automation solutions for modern factories. Our integrated solution consists of both on-prem infrastructure like full network stack (with switches, routers, firewalling) and Cloud-native software applications running on-prem and in the Cloud to operate and monitor the robotic assembly lines.
WHAT YOU WILL BE DOING
- Design, implement, and maintain reliable, scalable, and secure infrastructure to support applications and automation systems.
- Own and continuously improve platform engineering tools and services, including documentation and cross-team communication.
- Automate infrastructure provisioning, configuration management, and deployment pipelines.
- Manage CI/CD systems to enable efficient and reliable delivery of software.
- Implement and operate observability solutions (logging, monitoring, alerting) to ensure uptime and system performance.
- Enforce security best practices, including vulnerability management and incident response readiness.
- Participate in the on-call rotation for services owned by the Platform Engineering team.
WHAT WE WANT TO SEE
- Bachelor's or master's degree in computer science, engineering, or a related technical field
- At least 5+ years of experience in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).
- Strong experience with physical infrastructure, including networking equipment and servers.
- Proficiency with CI/CD tools and GitOps workflows.
- Hands-on coding experience in Python and Shell scripting.
- Solid understanding of Linux internals and system administration.
- Experience with public cloud providers (AWS, Azure, or GCP).
- Proficiency with Infrastructure as Code tools (Terraform, Ansible).
- Deep knowledge of Kubernetes (self-hosted and managed), including Helm.
- Familiarity with observability stacks (Prometheus, Grafana, OpenTelemetry).
IT WOULD BE NICE IF YOU HAD
- Experience with bare-metal provisioning (MaaS or similar)
BE EMPOWERED TO CHANGE AN INDUSTRY
Bright Machines is a next-generation, AI-enabled manufacturer focused on data center infrastructure production. Bright Machines uses its proprietary AI-based robotics and software to assemble AI infrastructure hardware products (i.e., data center servers) for hyperscalers, neoclouds, and leading Original Equipment Manufacturers (OEMs) to reduce their time to revenue. With its Bright Factory model, Bright Machines builds higher quality data center infrastructure at scale, addresses increasing market demands for computing power due to the surge of AI, and answers the call to the U.S. national mandate to reshore manufacturing.
Bright Machines is headquartered in the San Francisco Bay Area, California, and has an integration center in Guadalajara, Mexico. The company has been recognized as one of Forbes’ AI 50, awarded “Best AI-based Solution for Manufacturing” by AI Breakthrough, named a “Technology Pioneer” by the World Economic Forum, and highlighted by several other leading technology and innovation organizations.
Bright Machines San Francisco, California, USA Office
585 Howard St, San Francisco, CA, United States
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
