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H builds computer-use agents that take actions in browsers and desktop applications. You will own observability strategy, technical design, and rollout across the entire company stack, giving visibility into all systems and surfacing information critical for decision-making and progress tracking.
This is a hands-on lead role where you set direction, design the observability stack, lead others through implementation, and work with internal teams on adoption. You'll ensure teams measure what matters and develop deep knowledge of H's products and services.
Key responsibilities:
- Establish a unified observability strategy applicable across teams and technical stacks
- Own implementation of systems managing metrics, logs, traces, alerts, and dashboards
- Define SLAs, SLOs, and SLIs in collaboration with product, research, and infrastructure teams
- Build end-to-end visibility of system dependencies with visualizations for users and context for agents
- Automate tracking of coverage, reliability, alert quality, and execution costs
First-year milestones:
- Month 3: Every H product has SLAs, SLOs, and SLIs defined and measured in code with automated compliance reports
- Month 6: Single complete solution covers metric collection, log processing, and tracing
- Month 12: Every system at H uses the same SDKs and interfaces for alarms, metrics, logs, and traces
You'll collaborate across infrastructure, product, engineering, and research teams, reporting to the VP of Engineering.
The role is hybrid, requiring three days per week in either the Paris or London office with occasional travel between locations.
Requirements:
- Have set direction for substantial engineering work, delivered it, and achieved team adoption
- Built production instrumentation and telemetry integrations
- Defined both product-level and technical-level SLAs, SLOs, and SLIs
- Used SRE measurements including error budgets, burn rates, MTTA/MTTR/MTTM
- Built self-managed observability systems such as OTEL, Prometheus, Grafana, Loki, Mimir, Alloy, Elasticsearch, or Kibana
- Worked with Kubernetes at scale, enterprise multi-tenancy, inference, or asynchronous agent workflows
- No AI experience required; match on most criteria acceptable
