Senior Software Engineer, Infrastructure

You are a strong software engineer with an affinity for cloud infrastructure. An individual who is eager to learn about and solve a diverse set of infrastructure problems that are unique to a company that deals heavily with 3D data, computer vision, and machine learning. Someone who likes building internal tools and who thinks finding a simple solution to a hard problem is a high form of art. You are comfortable keeping up with an industry that is changing rapidly.

The Infrastructure team interacts with or owns everything past the application binary. The rest of engineering is our customer. Through automation, we strive to have the easiest path be the fastest and most secure path. We own, maintain, and advise on all cloud infrastructure such as our Kubernetes environment, databases, network, storage, and cache. All of engineering are our peers and we work with them to form consistent patterns for solutions to common architectural challenges around rich geospatial and machine learning workloads. We have a strong command over best practices for cloud architecture and CI/CD and use application development as a means to apply them.

Helping us build boring solutions to interesting problems while improving the platform that engineering teams build on.

You will work closely with engineers across the company to make their applications faster to deploy, easier to operate, and more reliable in production. You’ll collaborate with frontend, backend, computer vision, data, security, and machine learning teams to bring new ideas to production at scale. Because the team is small and highly collaborative, the work is varied and high-impact. You might be:

• Designing scalable cloud architecture
• Improving CI/CD pipelines or developer tooling
• Building Kubernetes platform capabilities
• Writing Helm charts or deployment automation
• Optimizing Docker images and container workflows
• Provisioning infrastructure using Terraform in GCP
• Improving observability, reliability, or security posture

Your work will directly improve the developer experience at Hover while helping build the platform that powers our computer vision and machine learning systems.

• 5–8+ years of professional software engineering experience, with meaningful time spent building or operating infrastructure, platform, or distributed systems
• Strong software engineering fundamentals with production experience in Go, Python, or Ruby
• Proven experience working with Kubernetes, including deploying and operating containerized workloads in production environments
• Hands-on experience with containerization technologies such as Docker, including building and optimizing container images
• Experience using Infrastructure as Code tools such as Terraform (strongly preferred), or configuration management tools like Ansible or Chef
• Experience working with cloud platforms such as GCP or AWS, with willingness to learn or deepen expertise in GCP
• A systems-oriented mindset; you think about reliability, observability, failure modes, and scalability when designing infrastructure
• Experience collaborating with engineers across teams to design platform capabilities or improve developer experience
• Comfort working across multiple parts of the infrastructure stack and learning new tools, technologies, and practices as the platform evolves

Hover has Hubs in San Francisco and New York City, where we expect that all employees living within a 50-mile radius of our offices will come into their local Hover office at least three times a week to build rapport and foster organic connection. At this time, Hover is not considering fully remote roles.

The US base salary range for this full-time position is $194,000 - $239,000 annually. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all applicable US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

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