Reports To: Director of Charging QualityThis role requires a full-time onsite presence in Durham, NC Target Base Range: $80 - 90k (Final compensation commensurate with experience and qualifications) Please note: We are only able to consider candidates who are U.S. citizens or lawful permanent residents (green card holders) and who do not require current or future visa sponsorship of any sort.Job SummaryThe NOC Engineer is the front line of quality intelligence for our DC fast-charging network. This role continuously reviews network performance, flags emerging trends, triages issues reported by Operations, Drivers, Automakers and other stakeholders, and validates assumptions with data before conclusions are drawn. Working across the full charging stack (charger hardware and firmware, CPMS backend, payment terminals, OCPP/OCPI/ISO 15118 protocol layers, and our internal data platform) the NOC Engineer performs evidence-based root cause analysis and delivers concise, prioritized feedback into the engineering group for all things quality-related: software bugs, feature gaps, and implementation gaps. The role partners daily with the Charging Quality team, Operations, Data/Technology teams, and our hardware, CPMS, and payment vendors.
Mission: Detect and triage the true root cause of issues impacting the customer charging experience, and convert network data into prioritized, actionable engineering feedback.
KPIs: - 1st Attempt Success
- Network MTBF / MTTR
- Time to Detect & Triage (detection lag from first occurrence to validated triage)
- RCA Quality (validated root causes; vendor/engineering escalations accepted on first submission)
Key Responsibilities - Network Monitoring & Trend Detection
- Review daily network performance against baseline (plug success, 1st attempt success, charge success, uptime, error-code frequency) and flag deviations before drivers or partners report them.
- Spot patterns across sites, charger models, firmware versions, vehicle OEMs, and failure modes; distinguish systemic regressions from site-local, vehicle-specific, or one-off events.
- Track customer-facing trends (repeat-visit failures, new vehicle behavior, Google/Plugshare commentary) and translate them into measurable, ticketed issues.
- Monitor the health of automated failure-mode classifiers; flag stale ingestion or classifier regressions that would distort KPIs before trends are misread.
- Issue Triage & Root Cause Analysis
- Triage incoming tickets from Operations: validate, complete, or correct initial assumptions with proof from raw data rather than accepting them at face value.
- Drive analysis to the true technical root cause using raw telemetry: OCPP message logs, application/server logs, payment terminal data, charger diagnostics, and session logs. Do not stop at surface-level dashboards.
- Correlate evidence across independent sources (telemetry, logs, vendor portals, customer reports) and reference the relevant standards (OCPP 1.6J, OCPI, ISO 15118, DIN 70121, IEC 61851).
- Document findings concisely on tickets with supporting queries, charts, and log excerpts, plus a short "how-to" so any teammate can retrace and verify the analysis.
- Engineering Feedback & Prioritization
- Provide concise, prioritized, evidence-backed input to the engineering group: software bugs, feature gaps, and implementation gaps, each with quantified customer impact (sessions affected, KPI impact).
- Recommend concrete next steps: lab replication steps, NOC runbook actions, config/firmware review, or field service dispatch.
- Validate fixes after release and watch for regressions when vendors ship new software.
- Vendor & Cross-Functional Escalation
- File well-evidenced tickets to hardware, CPMS, payment, and OEM partners; follow escalations through to closure.
- Surface recurring cross-ticket patterns to the Director of Charging Quality to feed the systemic-issue program and quality strategy.
- Propose monitoring, alerting, and classification improvements that shorten detection lag and reduce repeat analysis.
Qualifications - Bachelor's degree in engineering, computer science, data science, or related field, or equivalent hands-on experience.
- 3+ years in a NOC, network operations, reliability, data, or technical support engineering role within relevant industries (EV charging, energy, telecommunications, automotive, SaaS operations, or similar).
- Strong SQL and data analysis skills on large telemetry datasets; comfortable in BI/query tools (e.g., Superset) and log analysis platforms (e.g., Kibana/Elastic).
- Working knowledge of EV charging protocols and standards (OCPP 1.6J, OCPI, ISO 15118, DIN 70121, IEC 61851) or demonstrated ability to ramp quickly on protocol-level debugging.
- Disciplined, evidence-first root cause analysis: every assumption validated with data, alternatives ruled out, and conclusions reproducible.
- Excellent written communication: able to compress complex technical findings into short, prioritized, actionable summaries.
- Comfort building and using AI-assisted analysis workflows and automation as a daily force multiplier.
Success in This Role Looks Like - Emerging issues are detected and triaged from network data before customers, OEM partners, or vendors report them.
- Tickets reach engineering with a validated root cause, quantified impact, and clear priority, and require little rework.
- Detection lag shrinks measurably; wrong-cause escalations become rare.
- The NOC Engineer is the trusted voice of "what the network data says" in quality decisions and prioritization.
- While core hours follow a traditional business schedule, this position may occasionally require work outside standard business hours, including evenings and weekends, to support incident response or scheduled maintenance windows.
- Vendor escalations are accepted and actioned on first submission because the evidence package is complete.
IONNA is committed to fair and equitable compensation practices through a competitive base salary, as well as offering bonus programs, comprehensive benefits such as medical, dental, vision, life, 401(K), and paid holidays. Actual base salaries are based on several factors unique to each candidate, including but not limited to skill set, experience, certifications and specific work location.
