Night Shift Network Operations Center Noc Engineer Jobs in Raleigh, NC

The Systems Reliability Engineer serves as IONNA's technical investigation and quality intelligence function for customer charging failures. This role is responsible for determining why charging sessions fail, identifying systemic root causes across the charging ecosystem, and converting technical evidence into actionable engineering improvements.

Success in this role requires the ability to synthesize telemetry, logs, protocol transactions, customer-reported symptoms, and vendor data to develop evidence-based root causes and drive engineering action.

Mission

Detect, diagnose, and resolve the true root causes of charging failures and convert charging network data into prioritized, actionable engineering improvements.

  KPIs

• First Attempt Success
• Charge Session Success Rate
• Network MTBF / MTTR
• Time to Detect & Triage
• RCA Quality and Accuracy
• Engineering Escalations Accepted on First Submission

  Key Responsibilities   Charging Failure Detection & Analysis

• Monitor charging network performance and identify emerging customer-impacting issues before they become widespread. Detect patterns across charger models, firmware versions, vehicle OEMs, payment systems, and charging locations. Distinguish systemic issues from isolated site, vehicle, or environmental events.
• Translate customer complaints and operational observations into measurable technical investigations. Monitor the effectiveness of telemetry, analytics, and failure-classification systems.

  Root Cause Investigation

• Investigate charging failures using telemetry, charger diagnostics, session logs, backend application logs, payment data, and protocol transactions. Reconstruct charging-session timelines to determine where and why failures occurred. Validate or challenge assumptions using evidence from raw data rather than dashboards alone.
• Correlate findings across charger hardware, firmware, CPMS platforms, payment systems, vehicle communications, and backend services. Analyze protocol-level interactions including OCPP, OCPI, ISO 15118, DIN 70121, and IEC 61851. Document findings with supporting evidence and reproducible analysis.

  Engineering Feedback & Quality Improvement

• Deliver concise, evidence-based recommendations to Engineering. Quantify customer impact and business impact of identified issues. Identify software defects, implementation gaps, integration failures, protocol issues, and configuration problems.
• Recommend corrective actions including software fixes, firmware updates, monitoring enhancements, and process improvements. Validate fixes after deployment and monitor for regressions.

  Vendor & Cross-Functional Escalation

• Escalate issues to charger manufacturers, CPMS providers, payment vendors, OEMs, and technology partners with complete supporting evidence. Identify recurring patterns across incidents and surface systemic issues for prioritization.
• Recommend improvements to monitoring, alerting, and analytics that reduce detection and investigation time.

  Qualifications Required

• Bachelor's degree in Engineering, Computer Science, Data Science, Information Systems, or equivalent practical experience.
• A minimum of three years of experience performing root cause analysis of customer-impacting failures in software, hardware, IoT, automotive, payments, SaaS, or distributed systems environments.
• Proficient SQL and data analysis skills.
• Proven ability to diagnose issues using telemetry, logs, diagnostics, and system data to identify validated root causes.
• Experience with observability and log-analysis platforms such as Kibana, Elastic, Splunk, Datadog, Grafana, or similar.
• Ability to synthesize evidence across multiple systems and communicate findings clearly and concisely.

Preferred, but Not Required

• EV charging experience.
• Knowledge of OCPP 1.6J, OCPI, ISO 15118, DIN 70121, and IEC 61851.
• Experience with connected devices, automotive systems, IoT platforms, payment systems, or reliability engineering.
• Experience with BI and analytics tools such as Superset.
• Experience using AI-assisted analysis and automation workflows.

  Success in This Role Looks Like

• Emerging charging issues are identified before they become widespread customer problems. Charging failures are consistently traced to validated root causes rather than symptoms. Engineering receives actionable findings that require minimal rework.
• Vendor escalations are accepted and actioned because the evidence package is complete. Customer charging reliability improves through engineering changes driven by investigation insights.
• The Systems Reliability Engineer becomes the trusted voice of technical truth for charging quality and reliability across the organization.