GoPro helps the world to capture and share itself in immersive and exciting ways. We are a force for positivity, celebrating all things awesome while inspiring people to pursue their passions.

We celebrate diversity. We practice inclusion. We foster belonging. We demand equity. And we share the experiences of individuals and communities who also hold these values as core to who they are. From Bucharest to Munich, Silicon Valley to Shenzhen, we are dedicated to building a company that reflects and honors the diverse global communities where we live, work, and play.

Founded in 2002 by Nick Woodman, a photo and video enthusiast in search of a better way to film himself and his friends surfing, GoPro has grown into a relentlessly innovative brand loved around the world for its insanely versatile and enabling products.

As a Cloud Infrastructure Engineer, you will help build and run the cloud architecture behind GoPro’s subscription business and photo and video storage services, supporting every app session and automatic camera upload for a global customer base. You will use tools like Terraform and Kubernetes, along with AI agents and automated workflows, to keep our infrastructure secure, current, and reliable. You will join a distributed team of engineers and help shape how AI-augmented operations evolve at GoPro.

• Design, build, and operate automated patching and update workflows across our cloud infrastructure, including OS, container image, Kubernetes, and dependency updates, using AI agents and AI-assisted tooling to improve speed, safety, and coverage. • Build, deploy, and maintain AI agents and workflows that support infrastructure operations, including incident detection, triage, and response, with the goal of reducing manual on-call burden and MTTR. • Support web services, including our Ruby on Rails/Golang services, before they go live through activities such as production readiness reviews. • Maintain the health of live services by monitoring availability and latency metrics, log output, and container-level health signals. • Participate in blameless postmortems of outages and production problems to continually improve service reliability. • Perform scheduled or tactical operations to recover from faults across a wide variety of systems, for example Multi-AZ RDS failover, shifting request traffic across regions, or identifying and restarting failed Kubernetes pods. • Participate in an on-call rotation covering workdays and occasional weekends. • Help evolve our incident response strategy toward AI-augmented and automated approaches, turning recurring incidents into agents and workflows. • Contribute code changes to infrastructure, CI/CD, and observability tooling. • Collaborate closely with a distributed team of talented engineers to improve observability and availability against SLAs. • Contribute to planning activities, including agile story definition and work estimation.

• Bachelor’s or equivalent degree in Computer Science, Engineering, Information Technology, or a related field. • At least 5 years of professional experience in cloud infrastructure, with AWS expertise highly preferred, operating customer-facing production systems at significant scale. • Hands-on experience building or operating AI-driven automation in a real engineering environment, such as AI agents, AI-assisted patching or dependency updates, or AI-driven operational workflows. Recent experience, even within the past year, is valued. • Proven track record in highly collaborative environments requiring clear communication, regular updates, and technical communication via code review and change management. • Outstanding analytical and problem-solving skills for troubleshooting full-stack web services. • Demonstrable professional skills with most of the following technologies or their equivalents: Linux, Bash, Terraform, Python, Kubernetes, Helm, ArgoCD, Nginx, and AWS services including EC2 with Autoscaling, ALB, EKS, ECS, Spot Fleet, CloudWatch, CloudFront, RDS, and ElastiCache Redis/Valkey. • Experience with observability platforms such as Datadog, New Relic, or Sumo Logic. Bonus Points For • Experience deploying AI agents in production with monitoring, guardrails, and human-in-the- loop controls. • Experience using AI to automate patching or dependency updates across a production fleet. • Exposure to AI-native development patterns and AI-assisted platform operations. • Ruby on Rails and/or Golang experience.