Technical Product Manager (Observability)

Join Mirantis as a Technical Product Manager for k0rdent AI, our control plane for GPU infrastructure and distributed AI workloads. In this role, you will define the observability strategy, roadmap, and feature priorities, shaping how operators gain visibility into the health, performance, and resource utilization of GPU clusters. You will work directly with engineering, marketing, and customers to ensure their success. The ideal candidate has strong technical fluency in observability tooling and the AI infrastructure stack, with 5+ years of experience in product management or a senior technical role.

• Define the observability strategy, roadmap, and feature priorities for k0rdent AI, focusing on GPU clusters and AI workloads.
• Shape how k0rdent AI handles GPU-level metrics, distributed tracing, log aggregation, and intelligent alerting, leveraging OpenTelemetry and Prometheus.
• Manage the observability backlog, track emerging standards and technologies, and define integration strategies for vendor telemetry sources.

• The ideal candidate brings strong technical fluency in observability tooling and the AI infrastructure stack
• Fluency in Kubernetes observability, cloud-native monitoring, or metrics and alerting pipeline architecture
• 5+ years in product management or a senior technical role owning an observability product or operating large-scale monitoring infrastructure
• Working knowledge of Prometheus, OpenTelemetry, distributed tracing (Jaeger, Tempo), and log aggregation (Loki, Elasticsearch/OpenSearch)
• Ability to work directly with engineering on technical trade-offs and with field teams in competitive GPU cloud and NeoCloud deals
• Exposure to GPU observability, including DCGM metrics, AI workload profiling and performance analysis
• Familiarity with east-west fabric telemetry - InfiniBand counters, RoCEv2 congestion metrics (ECN, PFC, DCQCN), or switch-level fabric health
• Experience with high-performance storage telemetry from platforms such as VAST Data, Weka, or DDN, including IOPS, latency, and throughput instrumentation at scale
• Familiarity with NVIDIA BlueField DPU telemetry, SR-IOV, or offload pipeline observability
• Exposure to workload-level visibility for SLURM job scheduling, inference serving stacks (vLLM, Triton, TensorRT-LLM), or data service telemetry from vector databases (Milvus, Qdrant) and relational databases in AI pipelines