About the Role
At Camunda, we build the platform behind mission-critical process orchestration for customers worldwide. This role is central to that work. The Manager, Cloud Infrastructure Engineering leads the team that runs the cloud infrastructure behind Camunda's SaaS offering, keeping it reliable, scalable, and secure as the company grows. This is a hands-on engineering leadership role for someone who has built and run Kubernetes-based, multi-cloud infrastructure in production and can help a team do the same.
What you'll be doing
- Lead and grow the team that runs Camunda's SaaS cloud infrastructure, with a focus on execution and strong engineering culture.
- Guide the design, delivery, and evolution of Kubernetes-based, multi-cloud infrastructure, with reliability, scalability, and security as the baseline.
- Work with product engineering, security, support, and other engineering leaders to make sure the platform lets teams ship safely and efficiently.
- Keep raising the bar on infrastructure automation, developer tooling, and platform guardrails so the service scales without adding friction.
- Define how the team uses AI as a repeatable part of infrastructure work: ops analysis, automation, incident response, documentation.
- Balance day-to-day operational stability with longer-term investments in multi-cloud expansion and new infrastructure capabilities.
What you bring
- 3 - 5 years experience leading engineers who build and run production infrastructure for a SaaS product.
- Strong technical background in cloud infrastructure engineering, platform engineering, SRE, or a related domain.
- Hands-on Kubernetes experience in production, including scaling, reliability, and cluster lifecycle.
- Experience working across more than one major cloud provider and understanding the trade-offs of running multi-cloud.
- Track record of working with senior engineers and stakeholders across teams to deliver major infrastructure improvements while raising reliability, scalability and keeping a focus on security.
- Strong people leadership: coaching, managing performance, setting priorities, and building an environment where engineers can do their best work.
- Clear thinking about where AI fits in infrastructure engineering work, with judgment about what's useful, repeatable, and responsible.