vultr - Senior Technical Product Manager, Observability
Requirements
• 7+ years of product management experience in cloud infrastructure, observability, monitoring, or developer platforms • Deep understanding of observability and monitoring systems, including metrics, logging, tracing, alerting, and telemetry pipeline architecture • Experience defining product strategy and roadmaps for platform or infrastructure products at scale • Strong technical background — ability to engage with engineering on telemetry agents, data models, query engines, retention, and distributed systems • Experience with GPU, AI/ML, or HPC infrastructure monitoring and the unique observability challenges of training and inference workloads • Track record of shipping developer- and operator-facing products with measurable impact on reliability, time-to-detect, or operational efficiency • Experience working across cross-functional teams (engineering, design, marketing, sales) in a fast-paced environment • Excellent written and verbal communication skills, with the ability to translate complex technical concepts for diverse audiences • Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience)
Responsibilities
• Own the end-to-end Observability Platform roadmap across telemetry ingestion, querying, visualization, alerting, and retention for large-scale GPU clusters and multi-tenant cloud environments • Define Vultr's observability strategy across bare metal, VMs, Kubernetes, and managed services, aligned to infrastructure roadmap, reliability goals, and customer experience • Drive the customer-facing observability surface across dashboards, APIs, telemetry pipelines, and topology-aware insights • Translate low-level signals across GPU, CPU, memory, storage, and network into actionable health views, alerts, and debugging workflows for customers • Work closely with engineering on technical tradeoffs across metrics agents, collectors, data models, telemetry pipelines, APIs, and retention architecture • Build products for distributed AI environments by understanding how training and inference workloads behave across nodes, clusters, schedulers, and network fabrics • Define health models that help customers quickly identify degraded nodes, performance anomalies, and cluster bottlenecks at fleet scale • Ensure new infrastructure and platform launches are observable by design through strong partnership with compute, network, and platform teams • Stay current on modern observability stacks and AI infrastructure trends, including how GPU workloads change performance analysis, cost attribution, and operational workflows
Benefits
• $130,000 - $165,000 • Final compensation will vary depending on years of experience, background/skill set, location, and applicable laws. • INCLUSION & PRIVACY
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