Jobs at Gcore

Lead four engineering teams responsible for Gcore’s CDN control plane, edge and proxy layer, analytics and logging platform, DNS, and traffic management services. Own delivery planning, technical prioritization, incident response, on-call operations, service quality, hiring, and engineer development. The role requires strong understanding of internet infrastructure, distributed systems, HTTP caching, nginx, TLS, SNI, and anycast routing, plus experience managing distributed teams and driving post-incident improvements.

Monitor WAAP and DDoS activity, investigate alerts and false positives, analyze logs and traffic patterns, prepare customer-facing threat reports, escalate incidents, configure security policies during onboarding, meet reaction-time SLAs, and maintain operational runbooks. The role requires web security fundamentals, clear written English, attention to detail, and participation in shift or on-call rotations. Threat research and exploit development are explicitly outside the role’s scope.

Designs and develops Kubernetes-native AI infrastructure for inference and distributed model training. Responsibilities include writing Go-based controllers, operators, APIs, CLIs, and developer tools; optimizing serverless container workflows, GPU scheduling, autoscaling, reliability, security, and workload isolation; and monitoring Kubernetes ecosystem advancements. The role collaborates with technical teams to solve complex distributed-systems challenges and influence the product roadmap.

Design, build, and maintain a Go-based Traffic Management System API and edge agent to render/apply routing configuration. Implement routing (BGP/Anycast), automated failover, high-availability features, and strengthen reliability via tests, metrics, and observability while collaborating with cross-functional teams.

Design and build a managed Slurm service on Kubernetes, writing production-grade Go code for GPU-intensive workload scheduling and orchestration. Develop observability and automated remediation for GPU, node, network, and control-plane failures. Diagnose performance and reliability issues across HPC infrastructure, distributed storage, high-performance networks, and schedulers while preserving Slurm behavior and delivering a customer-focused platform.

Build and operate Python services and APIs for GPU virtual machines and bare-metal infrastructure. Develop provisioning, placement, maintenance, recovery, capacity, and scheduling workflows; integrate GPU servers with OpenStack and Kubernetes; automate validation and production readiness; and improve testing, observability, deployment safety, and operational tooling. Investigate complex production issues across compute, networking, storage, virtualization, and hardware while owning projects through rollout and ongoing operation.

Design, deploy, and maintain on-premises infrastructure for scalable AI inference workloads. Build GPU scheduling and model deployment pipelines, manage monitoring and observability systems, troubleshoot Kubernetes, Linux, networking, and production infrastructure, and collaborate with ML and platform teams on architecture and performance testing.

Lead design, deployment, and maintenance of edge infrastructure; ensure high availability, security, and performance; drive automation, observability, and incident response; mentor engineers and collaborate cross-functionally.

Process supplier invoices and accounting documents, reconcile vendor accounts, monitor accounts payable balances, maintain compliant documentation, prepare tax/audit support, record accruals and provisions, perform assets and inventory bookkeeping, and provide backup for other accounting functions.

As a Principal Support Engineer, you'll solve advanced technical issues in cloud infrastructure, lead incident responses, and mentor junior engineers while ensuring system reliability.

Perform hands-on troubleshooting and preventive maintenance on data center servers and GPU clusters, coordinate with vendors and data center staff, document hardware configurations and resolutions, and help develop hardware maintenance processes and spare-part management.