Member of Technical Staff (Cluster Management)

Requirements This role is for someone passionate about operating highly robust, observable, and automated systems and enabling customer successes

• Bachelor's degree in Computer Science, related technical field, or equivalent practical experience
• 5+ years of experience in Site Reliability Engineering, DevOps, or a similar role focused on large-scale production systems
• Deep expertise in SRE principles and practices, including SLOs, SLIs, operational automation, incident management, and post-mortems
• Extensive hands-on experience with public cloud platforms (AWS, GCP, Azure), including compute, networking, storage, and database services
• Strong experience with containerization technologies (Docker) and orchestration platforms (Kubernetes)
• Proficiency in designing and implementing robust monitoring, logging, and alerting systems using tools like Prometheus, Grafana, ELK stack, and distributed tracing
• Solid programming/scripting skills in at least one language (e.g., Python, Go) for automation and tool development
• In-depth knowledge of Linux operating systems, networking fundamentals, and system debugging
• Proven ability to troubleshoot complex issues across the entire stack
• Excellent communication, collaboration, and problem-solving skills
• Willingness to participate in on-call rotations
• (Desirable) Experience of managing data center grade GPU clusters with GPU (and peripherals like HBM and RDMA enabled networking) monitoring, troubleshooting, and fixing
• (Desirable) Experience with machine learning infrastructure, model serving, or distributed AI frameworks
• (Desirable) Hands-on experience in security and data protection

What the job involves As a Member of Technical Staff, Cluster Management at Fireworks AI, you will play a critical role in making our world-scale virtual AI cloud reliable, performant, and efficient

• You will apply your expertise in large-scale distributed systems, cloud infrastructure, and operational excellence
• You will partner closely with world-class software engineers and AI experts to scale cutting-edge AI platforms to meet the fast-growing demands and ever-evolving application paradigms
• Ensuring System Reliability: Ensure systems are designed and implemented with high availability, scalability, and performance. Focus on fault tolerance, disaster recovery, identifying and removing scaling bottlenecks, and performance optimization across our multi-cloud infrastructure
• Incident Management & Response: Lead efforts in incident detection, response, and resolution for critical production issues. Drive post-mortems to identify root causes and implement preventative measures to improve system reliability
• Observability & Monitoring: Develop, implement, and maintain comprehensive monitoring, alerting, logging, and tracing solutions to provide deep insights into system health and performance
• Automation & Toil Reduction: Identify and automate repetitive operational tasks to reduce toil and improve operational efficiency. Develop tools and scripts to streamline deployments, scaling, and system management
• Capacity Planning & Performance Tuning: Work proactively on capacity planning to ensure our infrastructure can gracefully handle growth and peak loads. Optimize system performance and resource utilization
• Reliability Best Practices: Collaborate with software engineers to embed reliability principles (e.g., SLOs, SLIs, error budgets) into the development lifecycle, promoting a culture of operational excellence
• On-call Rotation: Participate in a periodic on-call rotation to support our production environment and respond to critical alerts

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