DevOps Engineer

Neurophos • Austin, TX

17d • Onsite

About The Position

We are developing an ultra-high-performance, energy-efficient photonic AI inference system. We’re transforming AI computation with the first-ever metamaterial-based optical processing unit (OPU).
As AI adoption accelerates, data centers face significant power and scalability challenges. Traditional solutions are struggling to keep up, leading to rapidly rising energy consumption and costs. We’re solving both problems with an OPU that integrates over one million micron-scale optical processing components on a single chip. This architecture will deliver up to 100 times the energy efficiency of existing solutions while significantly improving large-scale AI inference performance.
We’ve assembled a world-class team of industry veterans and recently raised a $110M Series A led by Gates Frontier. Participants include M12 (Microsoft’s Venture Fund), Carbon Direct Capital, Aramco Ventures, Bosch Ventures, Tectonic Ventures, Space Capital, and others. We have also been recognised on the EE Times Silicon 100 list for several consecutive years.
Join us and shape the future of optical computing!
Location: Austin, TX. Full-time onsite position.
Position Overview:
We are seeking a DevOps Engineer to build and maintain the infrastructure and automation systems that support our hardware and software development teams. You will own our CI/CD pipelines, development environments, and deployment processes, ensuring our engineering teams can move fast while maintaining quality and reliability.

Requirements

• 3–7 years of professional experience in DevOps, site reliability engineering, or infrastructure roles
• Strong proficiency in Python (essential)
• Hands-on experience building and maintaining CI/CD pipelines (Jenkins, GitLab CI, GitHub Actions, or similar)
• Solid working knowledge of Linux systems administration
• Experience with Git workflows and repository management
• Comfortable writing scripts and tools to automate manual processes

Nice To Haves

• Experience supporting teams that develop both hardware and software (strongly preferred)
• Experience with machine learning development workflows, model training infrastructure, or ML pipelines (strongly preferred)
• Experience with on-premise automation systems that interface with lab or test equipment (strongly preferred)
• Experience with Docker and container orchestration (Kubernetes)
• Familiarity with AWS, GCP, or Azure
• Experience with Terraform, Ansible, or similar tools
• Familiarity with compiled language build systems (CMake, Make, Bazel)
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack)
• Exposure to embedded systems or firmware build and test processes

Responsibilities

• Design, implement, and maintain CI/CD pipelines for software builds, testing, and deployment
• Automate build processes for diverse codebases including firmware, drivers, and application software
• Implement automated testing infrastructure and integrate it into development workflows
• Create and maintain scripting and tooling to improve developer productivity
• Manage development infrastructure including build servers, test environments, and internal tools
• Provision and maintain cloud and on-premise resources for development and testing
• Implement infrastructure-as-code practices for reproducible environments
• Manage source control systems, artifact repositories, and package management
• Work closely with hardware and software teams to understand their tooling and infrastructure needs
• Support hardware bring-up and validation workflows with appropriate automation
• Provide technical guidance on DevOps best practices to engineering teams
• Document systems, processes, and runbooks for operational knowledge sharing

Benefits

• Competitive compensation, including salary and equity options.
• Good benefits - health, vision, dental, 401 (k), etc.
• Opportunities for career growth and future team leadership.
• Access to cutting-edge technology and state-of-the-art facilities.
• Opportunity to publish research and contribute to the field of efficient AI inference.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed