Software Engineer - Infrastructure

At Gravis, we build high tech systems that give machine operators super human capabilities. To adapt in real time to changes in the environment the Gravis Rack fuses data from LiDAR, cameras, GNSS, and hydraulics into an autonomous control system. As our engineering team grows we need world-class infrastructure to support the full development lifecycle of these systems: from developer tooling to continuous integration, testing, and deployment at scale.

As our software engineer with focus on infrastructure, you will be driving the requirements gathering, development, rollout and operation of the related infrastructure. The systems you build and operate power every line of code, commit, and production deployment at Gravis. You will work at the intersection of our Platform, Autonomy, Perception and Interface teams to enable high velocity & quality of developer workflows. At the same time, you ensure the continuous deployment of software to a fleet of 20-ton robots all across the world.

Responsibilities

• Design, build and operate end-to-end CI pipelines covering software builds, testing, linting, static analysis, versioning, releases, and deployment ranging from edge devices in the field to cloud infrastructure
• Own Configuration Management and infrastructure provisioning across the software department
• Collaborate closely with Autonomy and Perception engineers to understand requirements and translate them into reliable, scalable development environments for maximum development efficiency and velocity
• Own, operate and enhance in-office Hardware-in-the-loop test setups
• Own, operate and enhance fleet monitoring systems
• Closely collaborate with ML Ops Engineers and Simulation Engineers on shared infrastructure

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Engineering, Electrical Engineering, or a related field
• 3+ years of hands-on experience in Software Engineering, DevOps, data engineering, or similar roles
• Strong Software Engineering skills and solid experience with related tooling (e.g. clangd, cargo, pyrefly)
• Proven experience building and managing CI pipelines for build, test and ML workloads (e.g. GitHub Actions or GitLab CI)
• Proven experience with infrastructure as code (e.g. ansible, terraform)
• Proven experience with monitoring and observability tooling (e.g. grafana, prometheus)
• Hands-on experience with containerization (Docker).
• Experience with cloud platforms (AWS, GCP, or Azure).
• Experience with software packaging & versioning (docker images, debian packages).

Bonus Qualifications

Don't meet every requirement? We still want to hear from you. These are nice-to-haves, not dealbreakers:

• Experience working with robotics data (point clouds, camera streams, timeseries data).
• Experience with Robotics & DevOps related tooling (Foxglove, Prometheus, Grafana)
• Experience with Hardware-in-the-loop testing setups

This is an opportunity to join a dynamic and versatile team, and to be part of a young startup that will revolutionize heavy construction. Gravis Robotics offers a fair market salary and a working location in the vibrant city of Zurich. As a forward-facing startup, we understand that work-life balance and flexibility are important considerations for many professionals: If you are a highly qualified candidate with the requisite skills and experience, we encourage you to apply and discuss your preferred working arrangement during the interview process.

Gravis is an equal opportunity employer. We are committed to building an inclusive and diverse team, and do not discriminate based upon race, color, ancestry, national origin, religion, sex, sexual orientation, age, gender identity, gender expression, disability, veteran status, or other legally protected characteristics.

We are an international team that is working to solve problems with a global impact: to facilitate efficient communication and collaboration, proficiency in English is a requirement for all roles.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.