Senior Site Reliability Engineer

Job description

WHO WE ARE Hyperbolic Labs is on a mission to democratize AI by breaking down the barriers to computing power with our Open-Access AI Cloud. By aggregating computing resources across the globe, we offer an innovative GPU marketplace and AI inference service that promise affordability and accessibility for all. As pioneers at the intersection of AI and open-source technology, we believe in an open future where AI innovation is limited only by imagination, not by access to resources. We're looking for forward-thinking individuals who share our passion for making AI universally accessible, secure, and affordable. Join us in building a platform that empowers innovators everywhere to turn their visionary AI projects into reality. As we prepare for growth after our Series A, our team — led by co-founders with PhDs in AI, Math, and Computer Science — is poised to redefine computing. ABOUT THE ROLE We're seeking a Site Reliability Engineer to ensure Hyperbolic's GPU marketplace and AI infrastructure operate with exceptional reliability, performance, and security. As an aggregator of compute resources from hundreds of global suppliers, our SLOs, trust, and economic efficiency are product-critical. You'll be responsible for defining and maintaining service level objectives for job success rates, building robust incident response systems, managing capacity across our distributed GPU network, and implementing secure rollout and rollback mechanisms that keep our platform running smoothly 24/7. In this role, you'll establish the reliability standards that define customer trust in our platform, design monitoring and alerting systems that provide deep visibility into our infrastructure, build automation for capacity management and resource allocation, lead incident response and post-mortem processes, and work closely with engineering teams to improve system resilience. You'll also focus on security and infrastructure hardening, ensuring strong isolation between tenants and suppliers, implementing key management systems, and building compliance frameworks. This is a high-impact position where your work directly influences our ability to deliver on our promise of affordable, accessible AI compute at scale. WHO YOU ARE - Architected, deployed, and managed large-scale Kubernetes environments, including cluster administration, container orchestration, autoscaling, service discovery, and high-availability infrastructure to ensure reliability and scalability of mission-critical systems. - Led troubleshooting and performance optimization efforts across Kubernetes-based production environments, proactively identifying system bottlenecks, automating remediation workflows, and improving overall platform stability and uptime. - Strong automation mindset with experience using infrastructure-as-code, configuration management, and CI/CD pipelines - Strong background in capacity planning and management, including forecasting, resource allocation, and cost optimization for distributed systems - Experienced in incident response, on-call rotations, and post-mortem processes with a track record of reducing MTTR and improving system resilience - Deep knowledge of deployment systems including progressive rollouts, canary deployments, feature flags, and automated rollback mechanisms - Proficient in observability tools and practices including metrics, logging, tracing, and alerting systems (Prometheus, Grafana, ELK stack, or similar) - Strong understanding of infrastructure security including tenant isolation, workload isolation, network segmentation, and security hardening - Experience with secrets management, key management systems (KMS), certificate management, and secure credential rotation - Expert in site reliability engineering with proven experience defining, monitoring, and maintaining SLOs and SLAs for production systems - Knowledge of compliance frameworks and security best practices for cloud platforms (SOC 2, ISO 27001, or similar) - Excellent problem-solving skills with ability to debug complex distributed systems issues under pressure PREFERRED QUALIFICATIONS - Experience operating GPU infrastructure, AI/ML platforms, or compute marketplaces at scale - Background in distributed systems, peer-to-peer networks, or decentralized infrastructure - Knowledge of multi-tenancy security patterns, container security, and runtime security tools - Experience with chaos engineering, fault injection, and resilience testing - Familiarity with cost optimization strategies for cloud infrastructure and GPU resources - Experience building and operating systems with demanding uptime requirements (99.9%+ SLAs) - Background at companies like AWS, Google Cloud, Azure, or fast-growing infrastructure startups - Contributions to open-source reliability, observability, or security tools Hyperbolic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.