Apply on Employer Site

Phaidra · 6 hours ago

Senior Electrical Systems Specialist (Data Center Reliability)

United States

Full-time

Remote

Mid, Senior Level

$141K/yr - $211K/yr

3+ years exp

Phaidra is building the future of industrial automation by creating AI-powered control systems for the industrial sector. The Senior Electrical Systems Specialist will define and maintain electrical system ontologies for data centers, interpret telemetry data, and collaborate with teams to translate insights into actionable guidance for customers.

Artificial Intelligence (AI)Industrial AutomationInformation TechnologyMachine Learning

No H1B

Responsibilities

Define and maintain a domain-accurate electrical system ontology for data centers, ensuring customer system data reflects real-world electrical infrastructure, dependencies, and failure modes rather than abstract or purely data-driven representations

Apply deep knowledge of data center electrical systems to interpret telemetry from sensors, smart meters, and facility management systems, identifying early indicators of equipment degradation or abnormal behavior originating from customer-owned infrastructure

Specify, constrain, and validate analytical approaches—including statistical methods and machine learning—to detect anomalies in power usage, voltage stability, load behavior, and UPS/battery systems, ensuring outputs correspond to meaningful electrical risk rather than statistical novelty

Design and refine automated detection and alerting logic that mirrors how experienced operators reason about electrical system health, ensuring alerts correspond to actionable operational conditions such as unsafe load distributions, power anomalies, or loss of redundancy

Perform post-incident and post-anomaly analysis by correlating electrical, mechanical, and environmental signals to determine root causes and evaluate how accurately the product represented system behavior during customer incidents

Collaborate with customer-facing and product teams to translate anomaly insights into actionable guidance, helping customers recognize poor maintenance practices, reduce unplanned downtime, and improve overall reliability and PUE

Design, implement, and continuously refine rules-based electrical fault detection logic grounded in real data center operating experience, ensuring failure conditions are identified before they result in customer-visible impact

Grow internal expertise in data center electrical systems by sharing operational knowledge, failure patterns, and lessons learned from real-world infrastructure behavior

Qualification

Electrical power systemsData center environmentsAnomaly detectionMachine learningStatistical methodsSCADA systemsRules-based detection logicOperational excellenceEmpathyCommunication skillsCollaborationOwnership

Required

Minimum of 3 years of direct experience operating or monitoring electrical power systems within data center environments, including hands-on exposure to live, production infrastructure and participation in operational decision-making where uptime, redundancy, and recovery constraints materially influenced outcomes

Bachelor's degree in electrical engineering, power systems engineering, energy systems, or a closely related discipline or equivalent professional experience involving sustained, hands-on engagement with data center electrical infrastructure beyond purely procedural or observational roles

Deep, working understanding of data center electrical power systems—including power quality, load balancing, redundancy architectures (e.g., A/B paths), harmonics, fault detection, and protective relaying—sufficient to interpret abnormal behavior during live operations and translate those realities into product requirements or improvements

Proven ability to identify recurring electrical or operational patterns in data center environments and contribute to durable, scalable solutions—particularly by capturing lessons learned and applying them to system or product improvements

Ability to communicate complex electrical system behavior and operational risk clearly to both technical peers and non-domain stakeholders, particularly in post-incident analysis, product retrospectives, or reviews of how systems performed under stress

Demonstrated alignment with company values—Transparency, Collaboration, Operational Excellence, Ownership, and Empathy—especially in environments where reliability, trust, and learning from failure matter more than individual heroics

Demonstrated expert use of system telemetry, historical performance data, and real-time signals to assess data center electrical system health—particularly to evaluate how systems behave during maintenance or incident conditions and where standard operating procedures fall short

In your cover letter, please describe how your experience aligns with the qualifications listed above

Preferred

Proven experience analyzing, monitoring, and interpreting electrical distribution systems in data center environments, including substations, UPS systems, batteries, switchgear, PDUs, and stand-by generators, with a focus on understanding operational behavior and failure modes rather than day-to-day maintenance execution

Hands-on experience working with SCADA, BMS, or energy monitoring systems, including sensor integration and data acquisition, applied in a real-world operational context to understand system behavior and detect abnormal conditions

Experience designing and validating rules-based detection logic, thresholds, or analytics to identify electrical faults or abnormal operating conditions, grounded in practical operational experience rather than experimental modeling

Demonstrated ability to apply machine learning or advanced analytics as a tool to enhance fault detection, predictive insights, or energy optimization, with outputs validated against real electrical system behavior

Experience with time-series analysis, signal processing, or predictive modeling for power and thermal performance, applied to interpret real operational signals and guide actionable recommendations rather than generate research outputs