everlaw · Oakland, California, United States
Skills: Python, Java, AWS, Docker
The Role You'll build, modernize, and operate the platform-wide logging, metrics, and alerting infrastructure that gives Everlaw engineers real-time visibility into how our platform behaves in production. Working across the entire telemetry stack—from core libraries in Java and Python to ingestion pipelines, dashboards, and alerting—you'll ensure our engineering teams can detect, diagnose, and resolve issues while maintaining strict FedRAMP compliance and high availability. This is a full-time, exempt position based in our Oakland, CA office with a hybrid work schedule: in office M/W/Th with the option to work from home on Tu/Fr. What you'll do Build and maintain log, metric, and alert infrastructure across commercial and federal environments using tools such as Datadog, Grafana, Prometheus, and PagerDuty. Write reusable libraries and integrations in Java and Python that make it easy for engineers to emit structured logs, metrics, and traces from their services. Develop and manage infrastructure as code with Terraform to ensure dashboards, alert rules, and telemetry pipelines are versioned, reviewable, and reproducible. Improve our observability architecture by designing telemetry solutions that scale and incorporates emerging AI tools as Everlaw continues to grow. Improve alert quality and incident response by tuning noisy alerts, creating actionable runbooks, and helping engineers find the necessary signal during live incidents. Support regulatory and compliance efforts by keeping observability systems thoroughly documented and aligned with FedRAMP and data-handling requirements. Participate in on-call rotations, respond to production issues, and drive post-incident improvements to prevent recurrence. About You You have at least 2 years of professional software engineering experience building, testing, and operating production systems in a cloud environment (AWS preferred). You are proficient in a coding language such as Java, Go or Python and are comfortable pick…
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