• Design, implement, and evolve GCP-based infrastructure using Infrastructure as Code with Terraform and Google Cloud deployment automation patterns. • Build and maintain scalable CI/CD pipelines using Cloud Build, GitHub Actions, Jenkins, or equivalent platforms for application, infrastructure, and platform workloads. • Administer and optimize GCP delivery workflows including Cloud Build triggers, Artifact Registry, source integrations, deployment approvals, and service account access patterns. • Partner with engineering teams to improve build, release, and deployment workflows across microservices and cloud-native applications. • Implement robust observability across systems using Google Cloud Operations Suite, Cloud Logging, Cloud Monitoring, and related telemetry tooling. • Strengthen platform security by integrating secrets management, policy enforcement, vulnerability scanning, and least-privilege access control. • Manage and optimize containerized environments using Kubernetes, Helm, and Google Kubernetes Engine (GKE). • Drive reliability engineering practices including incident response, root cause analysis, SLO thinking, and automated remediation where appropriate. • Standardize reusable templates, modules, and platform patterns that improve developer productivity and consistency. • Mentor engineers and provide technical leadership on GCP architecture, deployment automation, release governance, and DevSecOps practices.

• Design, implement, and evolve Azure-based infrastructure using Infrastructure as Code with Terraform, Bicep, or ARM templates. • Build and maintain scalable CI/CD pipelines using Azure DevOps Pipelines for application, infrastructure, and platform workloads. • Administer and optimize Azure DevOps services, including Azure Repos, Pipelines, Artifacts, Boards, and service connections. • Partner with engineering teams to improve build, release, and deployment workflows across microservices and cloud-native applications. • Implement robust observability across systems using Azure Monitor, Log Analytics, Application Insights, and related monitoring tooling. • Strengthen platform security by integrating secrets management, policy enforcement, vulnerability scanning, and least-privilege access controls. • Manage and optimize containerized environments using Kubernetes, Helm, and Azure Kubernetes Service (AKS). • Drive reliability engineering practice, including incident responses, root cause analysis, SLO thinking, and automated remediation, where appropriate. • Standardize reusable templates, modules, and platform patterns that improve developer productivity and consistency. • Mentor engineers and provide technical leadership on Azure architecture, deployment automation, release governance, and DevSecOps practices.

• Contributing to long-term initiatives such as, but not limited to: Unlocking on-premises deployment of space algorithms with Kubernetes • Continuously improving the developer experience of your teammates (software and space) • Collaborating with space engineers and other software engineers to develop algorithms as services • Designing and developing core algorithms and infrastructure from early-stage prototypes to final deployment • Enhancing and extending the observability of our systems • Reviewing PRs and design documents, contributing to code via business-driven implementations and bug fixes, and reducing tech debt

Role Description Runware is building the API layer for the next generation of AI products. Our platform gives teams fast, reliable access to real-time inference across thousands of models through a single flexible API. We help customers build and scale media generation products with better performance, lower cost, and less operational complexity. We are looking for a Staff/Senior DevOps Engineer to help build, operate, and scale the infrastructure behind Runware’s global AI inference platform. You’ll play a critical role in making our systems faster, more resilient, easier to operate, and ready for the next stage of growth. As a Staff/Senior DevOps Engineer, you’ll help design, build, and operate the systems that power real-time AI inference across large-scale GPU fleets and a global production platform. This is not a traditional DevOps role; you’ll be working at the intersection of: - Bare-metal infrastructure - GPUs - Networking - Automation - Observability - High-performance distributed systems You’ll turn complex, hardware-driven infrastructure into reliable, automated, developer-friendly platforms. Your responsibilities will include: - Provisioning and orchestration - Deployment pipelines - Monitoring - Incident response - Capacity scaling You’ll build the foundations that let Runware scale with confidence: infrastructure that is fast, resilient, observable, secure, and built for the demands of real-time AI. Qualifications - Strong experience as a DevOps Engineer, SRE, Infrastructure Engineer, Platform Engineer or similar - Deep Linux knowledge and confidence debugging real production issues across networking, storage, performance, services and system behaviour - Hands-on experience building automation, Infrastructure-as-Code, CI/CD pipelines and deployment workflows - Experience operating high-availability, low-latency or high-throughput platforms - Strong networking fundamentals across TCP/IP, DNS, load balancing, routing, firewalls, proxies, TLS and HTTP - A calm and pragmatic approach under pressure - Strong communication skills and good judgement - Bias toward automation over manual toil Requirements - Build and scale the infrastructure that powers real-time AI inference across GPU fleets, bare-metal servers, serverless and containerised production systems - Help evolve Runware’s platform toward more elastic, on-demand infrastructure - Make Runware faster, more reliable and more resilient by improving critical paths - Automate the hard parts of infrastructure operations - Build the observability backbone for a high-performance AI platform - Play a leading role in production operations, incident response, debugging and post-incident improvements - Strengthen the security and compliance foundations of our infrastructure Benefits - Generous paid time off – vacation, sick days, public holidays - Meaningful stock options – share in the upside you create - Remote-first setup – work from home anywhere we can employ you - Flexible hours – own your schedule outside core collaboration blocks - Family leave – paid maternity, paternity, and caregiver time - Company retreats – twice-yearly gatherings in inspiring locations