Senior Observability Engineer

Verisign is seeking a Senior Observability Engineer to design and advance observability capability that transforms operational data into actionable insight. This role will create unified, “single pane of glass” experiences that enables executive decision makers, technology leaders, and application teams to understand system health, service performance, customer impact, and operational risks.

The ideal candidate combines deep observability engineering expertise with strong data-analysis and communication skills. They will establish application Service Level Indicators (SLIs), Service Level Objectives (SLOs), dashboards, and analytical models that connect technical performance to business outcomes.

This position is part of a highly skilled engineering and infrastructure team responsible for the design, administration, security, and operation of Verisign’s Architecture & Infrastructure Services (AIS) Team.  The position exists to strengthen our operational insights and enable key decision making through analytics. The role requires deep observability expertise combined with strong technical leadership. This individual will focus on improving observability, inherently improving system availability, reliability, and/or scalability of our shared services infrastructure.

The ideal candidate is outcome driven, leads across the stack, navigates the gap between engineering and executive layer, and can context switch seamlessly between executive presentation and all aspects of constructing concise dashboards.

Responsibilities:

Observability and Executive Dashboards:

• Design and maintain unified observability dashboards that consolidates metrics, logs, traces, events, and application/system data with the purview of Architecture and Infrastructure environments
• Develop executive-level views of service health, availability, performance, customer impact, operational risk, and capacity trends
• Translate complex technical data into clear insights that support prioritization, risk management, and operational decisions
• Define dashboard standards that provide consistent terminology, visualizations, service hierarchies, and health indicators
• Ensure dashboards emphasize actionable signals and trends rather than simply displaying large volumes of telemetry

SLO and SLI Engineering:

• Partner with application owners, product teams, and business stakeholders to define meaningful SLIs and SLOs
• Establish indicators for availability, latency, throughput, error rates, data quality, user experience, and critical business transactions
• Develop error-budget policies and reporting that help teams balance reliability, risk, and delivery speed
• Standardize SLO definitions, measurement methods, ownership, and governance across applications
• Automate the collection, calculation, visualization, and reporting of SLO performance
• Identify services that lack adequate monitoring or reliability targets and develop plans to close those gaps

Data Analysis and Operational Intelligence:

• Analyze observability data to identify performance degradation, reliability risks, recurring incidents, capacity constraints, and emerging trends
• Correlate technical telemetry with customer experience and business outcomes
• Develop health scores, trend analyses, anomaly detection, and predictive indicators.
• Perform deep-dive analysis to determine the root causes and broader patterns behind incidents and service degradation
• Produce concise operational insights and recommendations for executive and technical audiences
• Measure the effectiveness of observability investments using outcomes such as reduced detection time, faster recovery, fewer recurring incidents, and improved SLO attainment

Leadership:

• Serve as a senior technical authority for observability, monitoring, and reliability measurement
• Develop observability strategies, standards, roadmaps, and adoption models.
• Work with executives, architects, application teams, site reliability engineers, security teams, and operations leaders
• Coach engineering teams on instrumentation, dashboard design, SLO development, and data-driven problem-solving
• Lead technical evaluations and make recommendations regarding observability platforms and capabilities
• Promote a culture in which operational decisions are based on measurable service performance and customer impact

Requirements:

• Bachelor’s degree in Computer Science, Engineering, or equivalent work experience
• 10+ years of experience in observability engineering in observability engineering, site reliability engineering, platform engineering, production operations, or a related discipline
• Hands-on experience with enterprise observability platforms such as Splunk, Grafana, Prometheus, ELK, Nagios, Kafka, or comparable technologies
• Demonstrated experience defining and implementing application SLIs, SLOs, error budgets, and service-health measurements
• Strong experience analyzing metrics, logs, traces, events, and application-performance data
• Experience designing dashboards for both technical teams and executive decision makers
• Strong understanding of distributed systems, cloud platforms, microservices, containers, APIs, and application dependencies
• Experience with telemetry instrumentation and standards
• Proficiency with data-querying or analytical languages
• Experience automating observability configurations through APIs, scripting, infrastructure as code, or CI/CD pipelines
• Strong analytical, problem-solving, visualization, and communication skills
• Ability to translate technical findings into business impact, risk, and recommended action

Preferred Qualifications:

• Experience establishing or modernizing an enterprise-wide observability program
• Experience integrating observability data with Jira, ServiceNow, or similar operational platforms
• Familiarity with reliability engineering, incident management, capacity planning, and FinOps practices
• Experience developing service maps, application health scores, executive scorecards, or predictive operational analytics
• Knowledge of statistical analysis and anomaly detection
• Expertise operating and troubleshooting container platforms (Kubernetes, Docker)
• Relevant cloud, observability, SRE, data analytics, or platform-engineering certifications

This position is based in our Reston, VA office and offers a hybrid work schedule.

The pay range is $164,300 - $222,300.

The anticipated annual base salary range for this position is noted above, however, base pay offered may vary depending on job-related knowledge, skills, experience. Verisign offers a discretionary bonus which is based on individual and company performance, and certain roles may be eligible for discretionary stock awards.