Senior Kubernetes & Reliability Engineer
First seen by Alion on Oct 28, 2026.
At Verda, we're building a full-stack AI cloud, covering everything from data centers and hardware to our own cloud platform that the world's leading AI teams use to do serious AI work. We strive to make a positive mark on the world through the infrastructure we build and give leading teams a service they can truly depend on. Headquartered in Helsinki, we operate globally with offices in London and San Francisco. Join Verda while it’s still being built - not once it’s finished.
About the role
As Senior Kubernetes & Reliability Engineer you combine strong software development skills with hands-on experience operating production systems. You work with the team to build cluster management, observability, and automated delivery capabilities for our cloud-native infrastructure on Kubernetes, while exploring how AI agents can support diagnostics, troubleshooting, and operations automation.
Your responsibilities
Build Kubernetes platform capabilities: Contribute to the core development of Instant Cluster and automate cluster lifecycle management, including creation, configuration, scaling, upgrades, health checks, and decommissioning.
Improve production reliability: Take part in incident response, troubleshooting, and post-incident reviews. Improve capacity planning, change management, recovery procedures, and runbooks, turning recurring issues into platform improvements.
Strengthen observability: Build and improve metrics, logging, tracing, and alerting for clusters and platform services. Define health indicators and service level objectives (SLOs) for key services so the team can detect and diagnose issues more efficiently.
Put GitOps into practice: Manage applications and infrastructure through declarative configuration, version control, and continuous reconciliation. Improve delivery across environments, configuration drift detection, change review, and recovery from failed changes.
Advance engineering quality and automation: Develop maintainable platform services and operational tools, and contribute to design reviews, code reviews, and testing. Explore AI-assisted diagnostics and operational workflows based on practical needs.
Your key competencies
5+ years of experience in platform engineering, infrastructure engineering, SRE, or a related field, or demonstrably equivalent expertise, driving projects independently from design through deployment and maintenance
Deep Kubernetes expertise: building, maintaining, and troubleshooting production clusters, with real depth in at least one of control plane, scheduling, networking, storage, or node lifecycle, including complex failures and upgrades
Strong software development skills in Go, Python, or similar, building production-grade services and automation, with care for API design, idempotency, retries, error recovery, and testing
A solid foundation in production operations: Linux, networking, and distributed systems, with experience of incidents, releases, and capacity. You can explain how you diagnosed an issue, restored service, and followed up with improvements.
Practical observability experience with Prometheus, Grafana, or comparable systems, using metrics, logs, and traces together to investigate issues and design alerts people act on
GitOps in practice: declarative configuration, version control with Git, continuous reconciliation, and configuration drift, applied to Kubernetes delivery and operations
Collaboration and ownership: communicating proposals and risks clearly, making sound trade-offs between reliability, speed, cost, and complexity, and sharing knowledge through documentation and reviews
Nice to have
Managed Kubernetes services, container platforms, multi-cluster management, or customer-facing infrastructure products
Kubernetes Operators or controllers, Cluster API, or cloud provider API integration
Hands-on with Argo CD or Terraform, or open-source contributions to cloud-native projects
Secrets management tools such as OpenBao
GPUs or GPU infrastructure
LLM-based tools or AI agents for diagnostics, troubleshooting, or operations automation
Why Verda
Cash and equity compensation along with local benefits.
40+ nationalities, with 6 different ones on the management team.
A real chance to make an impact and work alongside world class engineers, researchers, and partners across the global AI ecosystem.
Practicalities
Location: London (UK) or Helsinki (Finland), where we have offices. If you're based elsewhere in Europe, this role can also be done remotely from the EU.
Employment type: Full time and permanent
We're building fast and this role needs the right person behind it. There's no artificial deadline, but when we find who we're looking for, we move. If this sounds like your next move, apply now.
When you apply, we’d love to hear about the production clusters or platforms you have been responsible for, complex incidents you have resolved, and how you turned repetitive operational work into automation. Links to open-source contributions or relevant projects are welcome too.
Please submit your application through our Careers page. We don't accept applications sent by email.