Senior Engineering Manager, Observability Engineering

Own the team's technical roadmap and delivery, aligned with broader engineering priorities. Evaluate build, buy, and open-source options, balancing reliability, customer needs, and cost .

• Technical leadership:

Lead, hire, and grow a high-ownership team of engineers. Guide technical decisions through design and code reviews. Coach engineers, help them grow, and clear the friction that slows them down.

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• Proven experience leading engineering teams that build and operate observability, monitoring, or telemetry platforms at scale, with strong operational practices.

• Demonstrated success leading engineering teams that build and operate production observability platforms, including hiring, coaching, performance management, and delivery.

• 15+ years in software and/or infrastructure engineering, including 7+ years of people management, with demonstrated ownership of delivery and live-site outcomes.

• Experience hiring, leveling, and performance management.

• Strong distributed-systems expertise with the hands-on judgment to guide architecture and execution rather than guide it from a distance.

• Experience operating multi-tenant infrastructure that other people's production workloads depend on.

• Bachelor's degree in Computer Science or related field, or equivalent practical experience; advanced degree a plus.

• Excellent communication skills, with the ability to partner across engineering, product, and leadership and translate customer feedback into a roadmap.

• Strong leadership and coaching; ability to grow engineers and build a healthy, accountable, high-ownership team, including through reorgs, acquisitions, or platform migrations.

• Set priorities and deliver incremental improvements with incomplete information. Make tradeoffs explicit and adapt plans as customer and operational needs change.

• Command of the observability building blocks - metrics, logs, traces, profiling, and alerting and the tradeoffs between them at scale.

• Time-series and telemetry data fundamentals: cardinality control, retention and downsampling, query performance, and hot/cold storage tiering.

• Live-site reliability craft: SLA/SLO definition, on-call, incident management, and postmortem-driven continuous improvement.

• Ability to review and raise the bar on technical artifacts (design docs, code reviews) across a distributed-systems codebase.

• Applying AI/LLM techniques to triage, anomaly detection, or incident summarization, with clear-eyed judgment about where they help and where they don't.

• OpenTelemetry at depth: collector architecture, semantic conventions, instrumentation strategy.

• The open-source observability stack in production: Prometheus, Mimir/Thanos/Cortex, Grafana, Loki, Tempo, ClickHouse.

• Building observability as a product for external developers, not only as internal tooling.

• Kubernetes internals and multi-cloud delivery across AWS, GCP, and Azure.

• Vendor consolidation or migration programs (commercial APM/SaaS to open-source, or the reverse) with measurable cost and reliability outcomes.

• Developer experience or engineering productivity backgrounds - treating internal engineers as customers with a measurable experience.

• Prior experience at a developer infrastructure or open-source-based company, where the community is part of the feedback loop.

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