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Quavo Fraud & Disputes

Site Reliability Engineering Lead

Posted 9 Hours Ago
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Remote
Hiring Remotely in United States
160K-180K Annually
Senior level
Remote
Hiring Remotely in United States
160K-180K Annually
Senior level
Leads Quavo’s site reliability and application monitoring function, owning alert detection, routing, severity standards, signal quality, and remediation accountability. The role manages Datadog, CloudWatch, Snowflake alerting, Uptime.com, and PagerDuty; establishes SRE practices including SLOs, incident command, runbooks, and capacity reviews; coordinates production readiness and releases; leads incident response; and automates diagnostics and remediation across SaaS applications, cloud infrastructure, integrations, and data layers.
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Who we are:

Quavo is the industry leader in fraud and disputes management technology, offering the world’s only E2E cloud-based Disputes as a Service solution for issuing financial services organizations. Quavo is an organization of tenacious experts who are innovative and challenge complacency to continuously deliver cutting edge technology and AI. Our experts are passionate about delivering value in our solutions and empowering our client community to enhance and evolve industry standards in fraud and disputes management.



About the role:

The Site Reliability Engineering Team Lead owns application monitoring at Quavo: what gets detected, how alerts are routed, and how good the signal is. No team has been accountable for this until now, so monitoring has been assigned by where an incident started and has lapsed or been duplicated afterward. Reporting to the VP of Engineering, the role connects Product, Infrastructure, and Support through clear routing and agreed severity standards, with authority to assign remediation to the owning group. The result is that Quavo finds issues before clients report them, and every alert has an owner before it fires.

Responsibilities include:

  • Establish and refine the SRE operating model with Product, Infrastructure, and Support: alert lifecycle, severity and response targets.
  • Own detection end to end what is monitored, alert thresholds and content, and signal quality. Tune or retire noisy monitors and keep coverage from lapsing after incidents close.
  • Route every alert to its owning group through PagerDuty, triage alerts with no mapped owner, assign remediation work, and verify closure.
  • Own the monitoring and paging stack (Datadog, Amazon CloudWatch, Snowflake-based alerting, Uptime.com, PagerDuty) and apply software engineering to reduce toil through runbooks and automation.
  • Run production readiness reviews and release coordination, and build the team over time, introducing SLOs, incident command, and capacity reviews as signal quality and capacity allow.

Required Qualifications:

  • 5-10 years of experience in SaaS, application operations, production support, SRE, or observability
  • Experience leading, mentoring, or coordinating a production operation, application support, SRE, observability, or monitoring team.
  • Hands-on experience running customer-facing SaaS in production and troubleshooting across applications, platforms, integration, data, and cloud layers, with working knowledge of AWS and distributed architectures.
  • Working knowledge of SRE principles: service-level indicators and objectives, error budgets, toil reduction, and blameless post-incident review.
  • Strong monitoring experience with Datadog, Amazon CloudWatch, or similar (Prometheus, Grafana, OpenTelemetry), including dashboards, synthetic tests, alerting, and PagerDuty.
  • Ability to establish ownership and routing across teams without owning their work, and to influence senior leaders, including through escalation, with strong communication and judgment.
  • Experience leading incident response, root cause analysis, runbooks, and corrective actions.
  • Ability to automate diagnostics, monitoring, or remediation with Python, PowerShell, Bash, APIs, or similar tools, as sustained engineering work rather than one-off scripts.

Preferred Qualifications:

  • Experience defining and operating SLIs, SLOs, or error budgets in production.
  • Kubernetes/EKS and containerized application operations.
  • Experience monitoring complex workflows, integrations, or data pipelines, including Snowflake.
  • Experience establishing an SRE or monitoring-ownership function where none existed.


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