Infrastructure Software Engineer

Overland AI•Seattle, WA

2d•$120,000 - $200,000•Hybrid

About The Position

Overland AI is building off-road autonomy, and our software infrastructure is the backbone that enables our teams to move fast, experiment safely, and ship mission-critical systems. As a Software Infrastructure Engineer, you’ll design, build, and maintain the internal software systems that power our AI/ML workflows, connect our robots, and streamline developer operations across the company. You will own core services used daily by researchers, roboticists, and field teams — including internal APIs, experiment tooling, data systems, and compute orchestration. This role is ideal for an engineer who loves building robust systems, improving developer velocity, and shaping the foundation that our autonomy stack relies on. You’ll collaborate closely with the infrastructure team, ML teams, and robotics teams to build reliable, observable, well-structured systems in a hybrid cloud/on-prem environment.

Requirements

5+ years of experience in software engineering, infrastructure tooling, or full-stack development
Proficiency with modern web frameworks and the ability to build both backend and front-end systems
Experience building and maintaining both microservices and monolithic applications
Strong working knowledge of AWS, Linux systems, and networking fundamentals
Proficiency with containerized environments (Docker/Kubernetes) and CI/CD (GitLab, GitHub Actions, or equivalent)
Experience with infrastructure-as-code (Terraform, Ansible, etc.)
Demonstrated ability to support multiple internal or customer-facing applications simultaneously
Excellent troubleshooting skills across software, networking, and infrastructure layers
Strong communication and documentation skills

Nice To Haves

Experience supporting and optimizing CI/CD pipelines and workflows
Experience with Kubernetes or GitOps tools (ArgoCD, Flux, Spinnaker)
Familiarity with ML infrastructure, experiment tracking, or data visualization tools
Experience with hardware integration or embedded system interfaces
Prior experience supporting hybrid or on-prem deployments
Experience migrating a monolith to a microservices-based architecture

Responsibilities

Design, build, and maintain internal services and tooling used across AI/ML, autonomy, and field operations teams
Develop both backend services and front-end interfaces (web apps, dashboards, APIs) that enable experimentation, data access, and compute management
Build and support microservices as well as monolithic systems, including migrating legacy systems to modern service-oriented architectures
Improve developer velocity and system reliability through better tooling, automation, observability, and CI/CD
Support hybrid deployments across AWS, on-prem compute, and on-robot environments
Troubleshoot across software, infrastructure, and networking layers to keep internal systems reliable and performant
Collaborate with ML engineers, roboticists, and internal stakeholders to define requirements and deliver high-impact tooling
Maintain excellent documentation and support distributed teams (local + remote + field)