Principal Solutions Architect - Observability and AI

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future. Department Overview asfafsafvd Job Description We are seeking a visionary Principal Systems Architect to design and scale our next-generation observability and reliability frameworks. You will champion modern telemetry practices, build predictive monitoring systems, and ensure our infrastructure meets the highest standards of high availability. Basic Requirements Key Responsibilities Architect Observability Frameworks: Design end-to-end telemetry systems focusing on metrics, logs, and traces. Implement Advanced Analytics: Build anomaly detection engines using system KPIs to catch issues before impacts occur. Drive Predictive Analysis: Deploy machine learning or statistical models to forecast capacity and system degradation. Design KPI Dashboards: Create intuitive, multi-tier visualization dashboards offering both high-level system health and granular component views. Enforce High Availability: Establish architectural patterns aligned with "Five Nines" (99.999%) availability principles. Define Service Metrics: Establish SLA, SLO, and SLI frameworks across distributed engineering teams. Required Technical Skills Observability Stacks: Deep expertise in Datadog, OpenTelemetry, or Prometheus/Grafana. Data & Analytics: Strong hands-on experience with statistical analysis, time-series data, and predictive alerting. Cloud Architecture: Advanced knowledge of AWS, Azure, or GCP infrastructure and microservices scaling. Reliability Engineering: Proven track record of designing fault-tolerant, self-healing distributed systems. AIOps skills Anomaly Detection Systems – Design algorithms to spot baseline deviations instead of relying on static, manual alert thresholds. Correlative Root-Cause Analysis – Build systems that automatically link spikes in metrics to errors in logs and traces. Predictive Capacity Planning – Use time-series forecasting to predict infrastructure bottlenecks and auto-scale resources before failures occur. Alert Noise Reduction – Implement ML-driven event deduplication and grouping to eliminate alert fatigue. Leadership skills Proven ability to mentor engineering teams and communicate complex technical concepts to Leadership team. Education Qualification Bachelor's degree in comptuter scienece or Electronics Engineering Travel Requirements None Relocation Provided None Position Type Experienced Referral Payment Plan Yes EEO Statement Motorola Solutions is an Equal Opportunity Employer.