Senior DevOps Engineer

Type: Permanent / Full-Time (Employment or Contract considered)

Location: Remote or Hybrid

Time Zones: UK, Europe, North America–friendly

We’re working with a high-growth tech-start up company building a next-generation AI cloud platform, focused on fast, reliable inference for large language models and other compute-intensive workloads.

The platform combines modern cloud infrastructure, Kubernetes, GPU clusters, and developer-first tooling to support mission-critical AI systems operating across multiple regions.

They’re now looking for a Senior DevOps Engineer to take ownership of the infrastructure backbone — someone who enjoys operating complex systems at scale and working closely with infrastructure, ML, and product engineering teams.

• Design, build, and operate highly available, secure infrastructure supporting AI inference, fine-tuning, and data processing workloads
• Manage multi-region Kubernetes clusters, including GPU-heavy environments
• Implement autoscaling strategies across heterogeneous compute fleets

• Own and evolve infrastructure-as-code using tools such as Terraform, Helm, and similar
• Automate provisioning of compute, networking, and storage
• Build tooling to spin environments up and down for experiments, benchmarks, and customer deployments

• Design and maintain CI/CD pipelines across backend, infrastructure, and ML components
• Implement safe deployment strategies (e.g. blue/green, canary releases)
• Partner with engineers to improve build speed, test reliability, and deployment confidence

• Build and operate observability stacks (metrics, logging, tracing)
• Define and monitor SLOs / SLAs for latency, availability, and reliability
• Create runbooks, playbooks, and incident response processes for production systems

• Implement best practices around secrets management, access control, and network security
• Support secure, multi-tenant environments for enterprise customers
• Help foster a culture of operational excellence, ownership, and reliability

• 4–8+ years’ experience in DevOps, SRE, Platform, or Infrastructure Engineering
• Strong experience running production systems on major cloud platforms (AWS, GCP, or Azure)
• Deep hands-on experience with Kubernetes in production
• Strong Infrastructure-as-Code skills (Terraform or equivalent)
• Proficiency in at least one scripting or programming language (e.g. Python, Go, Bash)
• Solid understanding of networking, security fundamentals, and distributed systems
• Proven experience building reliable, observable, automated systems

• Experience supporting GPU-based workloads or ML infrastructure
• Exposure to AI / ML platforms, inference systems, or data pipelines
• Familiarity with modern CI/CD tooling and GitOps approaches
• Experience with observability tooling (metrics, logs, tracing)
• Background in cloud platforms, AI infrastructure, or high-scale SaaS environments

• Work on core infrastructure powering cutting-edge AI systems
• High impact and ownership over architecture and tooling decisions
• Collaboration with senior engineers across infrastructure, ML, and product
• Competitive compensation, equity, and long-term growth potential
• Flexible remote / hybrid working