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Remote Electrical Reliability Engineer Jobs (NOW HIRING)

AWS DevOPS/SRE Engineer

Norfolk, VA · Remote

$58.25 - $77.50/hr

AWS DevOPS/SRE Engineer REMOTE Top Skills Required : Devops Eng with strong AWS experience - DevOps/SRE related AWS, Terraform, Kubernetes, Monitoring / Responsibilities : Key Responsibilities ...

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Site Reliability Engineer

Westlake, TX · On-site +1

$54.75 - $72.75/hr

We are currently seeking a Site Reliability Engineer to join our team in Westlake, Texas (US-TX), ... The starting pay range for this remote role is 85,000-140,000 This range reflects the minimum and ...

Electrical Engineer (EE) The Position The Electrical Engineer (EE) for Above Group shall contribute ... This is a remote position. Local candidates will be given the option to work in the office, remote ...

$104K - $127K/yr

Basic Requirement for an Electrical Engineer (Reliability Compliance) position: Degree: Bachelor's degree (or higher degree) in engineering. To be acceptable, the program must: (1) lead to a bachelor ...

Site Reliability Engineer

Westlake, TX · On-site +1

$54.75 - $72.75/hr

We are currently seeking a Site Reliability Engineer to join our team in Westlake, Texas (US-TX), ... The starting pay range for this remote role is 85,000-140,000 This range reflects the minimum and ...

Site Reliability Engineer

WV · Remote

$164K - $215K/yr

Yes GDIT is seeking a Site Reliability Engineer (SRE) to help ensure the resilience, performance ... Remote Travel= 25-50% Expected The likely salary range for this position is $164,382 - $215,050.

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Remote Electrical Reliability Engineer information

See salary details

$50.5K

$111.1K

$168K

How much do remote electrical reliability engineer jobs pay per year?

As of Jul 10, 2026, the average yearly pay for remote electrical reliability engineer in the United States is $111,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,000.00 and $132,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Electrical Reliability Engineer vs Remote Maintenance Engineer?

AspectRemote Electrical Reliability EngineerRemote Maintenance Engineer
Required CredentialsElectrical engineering degree, reliability certificationsTechnical diploma or degree, maintenance certifications
Work EnvironmentIndustrial facilities, power plants, manufacturing sites (remote monitoring)Factories, plants, equipment sites (remote or onsite)
Industry UsagePower, manufacturing, energy sectorsManufacturing, industrial sectors
Search & Comparison IntentFocus on reliability, system optimization, diagnosticsFocus on repairs, preventive maintenance, equipment troubleshooting

The Remote Electrical Reliability Engineer primarily focuses on ensuring electrical systems' reliability through diagnostics and system optimization, often working remotely with data analysis. In contrast, the Remote Maintenance Engineer emphasizes equipment repairs and preventive maintenance, which may involve more hands-on tasks or remote oversight. Both roles are vital in industrial sectors but differ in their core responsibilities and skill sets.

More about Remote Electrical Reliability Engineer jobs
What cities are hiring for Remote Electrical Reliability Engineer jobs? Cities with the most Remote Electrical Reliability Engineer job openings:
What are the most commonly searched types of Electrical Reliability Engineer jobs? The most popular types of Electrical Reliability Engineer jobs are:
What states have the most Remote Electrical Reliability Engineer jobs? States with the most job openings for Remote Electrical Reliability Engineer jobs include:
What job categories do people searching Remote Electrical Reliability Engineer jobs look for? The top searched job categories for Remote Electrical Reliability Engineer jobs are:
Infographic showing various Remote Electrical Reliability Engineer job openings in the United States as of July 2026, with employment types broken down into 93% Full Time, 5% Part Time, 1% Contract, and 1% Nights. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $111,091 per year, or $53.4 per hour.
Solution Architect AI Platform Reliability & SRE (Mythos SRE)

Solution Architect AI Platform Reliability & SRE (Mythos SRE)

Imagine Staffing Technology

Buffalo, NY • Remote

$55.25 - $73.50/hr

Full-time

Posted 10 days ago


Job description

Job Title: Solution Architect – AI Platform Reliability & SRE (Mythos SRE)
Location: Remote (Within USA)
Hire Type: Contract
Pay Range: Competitive Hourly Rate
Work Model: Remote with periodic travel to Buffalo, NY
Schedule: Monday – Friday, Standard Business Hours
Recruiter Contact: Samantha Marranca | 716-256-1271 | smarranca@imaginestaffing.net
NO C2C, NO sponsorship given at this time
Nature & Scope:
Positional Overview
Our client is seeking an experienced Solution Architect to support the reliability, scalability, observability, and operational excellence of its enterprise AI platform, Mythos. This role serves as the solution architecture extension of Enterprise Architecture and AI Platform teams, translating strategic platform designs into detailed operational architectures that enable highly available, resilient, and scalable AI services.
The Solution Architect will partner closely with Site Reliability Engineering (SRE), Platform Engineering, Infrastructure, Cloud Operations, and Application Development teams to establish architecture patterns and operational frameworks that support enterprise AI workloads across cloud and co-location environments.
This position is ideal for a hands-on architect with expertise in cloud infrastructure, platform engineering, observability, reliability engineering, and large-scale distributed systems.
Role & Responsibility:
Tasks That Will Lead To Your Success
AI Platform Reliability Architecture
  • Translate enterprise AI platform architecture into detailed operational and infrastructure solution designs.
  • Define reliability, scalability, resiliency, and availability architecture standards for AI workloads.
  • Develop architecture patterns supporting highly available and fault-tolerant AI services.
  • Support enterprise AI platform growth through scalable infrastructure and platform design.
  • Establish architecture guidance for production readiness and operational excellence.
Site Reliability Engineering & Operational Excellence
  • Define architecture patterns supporting SRE best practices across AI platforms.
  • Support implementation of Service Level Indicators (SLIs), Service Level Objectives (SLOs), and error budget frameworks.
  • Develop operational readiness standards and deployment validation processes.
  • Establish reliability engineering practices that improve system stability and performance.
  • Partner with engineering teams to improve incident prevention, detection, and response capabilities.
Scalability & Performance Optimization
  • Design solutions supporting large-scale AI workloads and model-serving environments.
  • Establish architecture patterns that optimize platform performance and resource utilization.
  • Support capacity planning and infrastructure scaling strategies.
  • Identify performance bottlenecks and recommend architectural improvements.
  • Collaborate with engineering teams to improve application and platform efficiency.
Observability & Monitoring
  • Design enterprise observability frameworks supporting AI platform operations.
  • Establish telemetry standards providing visibility into system health, model performance, operational metrics, and risk indicators.
  • Define monitoring, alerting, logging, and tracing strategies.
  • Support implementation of observability tools and telemetry platforms.
  • Ensure operational teams have actionable insights supporting platform reliability and performance.
Infrastructure & Automation
  • Develop architecture guidance for Infrastructure as Code (IaC) and platform automation.
  • Support CI/CD pipeline architecture and deployment automation strategies.
  • Establish repeatable operational patterns supporting cloud and co-location environments.
  • Promote infrastructure standardization and operational consistency.
  • Collaborate with Platform Engineering teams on automation and operational tooling initiatives.
AI Operational Governance
  • Support architecture strategies for AI model monitoring and drift detection.
  • Establish operational frameworks supporting AI governance and platform controls.
  • Define reliability patterns for embedded AI capabilities within enterprise applications.
  • Ensure platform operations align with enterprise security, compliance, and risk management standards.
Cross-Functional Collaboration
  • Partner with Enterprise Architects, Platform Engineering, Infrastructure, Security, Observability, and Development teams.
  • Participate in architecture reviews, design workshops, and Agile ceremonies.
  • Provide technical guidance throughout the SDLC from design through production deployment.
  • Validate architecture decisions and ensure adherence to enterprise reliability standards.
  • Contribute operational insights that influence future platform architecture decisions.
Skills & Experience
Qualifications That Will Help You Thrive
Required Experience
  • Bachelor’s Degree in Computer Science, Information Technology, Engineering, or related discipline.
  • 5+ years of experience in Solution Architecture, Site Reliability Engineering, Platform Engineering, DevOps, or Cloud Architecture.
  • Experience designing highly available, scalable, and resilient distributed systems.
  • Strong understanding of cloud infrastructure and platform architecture principles.
  • Experience supporting production operations and enterprise-scale technology environments.
  • Knowledge of observability, monitoring, logging, and telemetry frameworks.
  • Experience with Infrastructure as Code and deployment automation concepts.
  • Strong communication and stakeholder management skills.
Preferred Qualifications
Experience supporting AI, Machine Learning, or Generative AI platforms.
Experience with Kubernetes, container orchestration, and cloud-native technologies.
Familiarity with observability platforms such as Datadog, Dynatrace, Grafana, Prometheus, Splunk, or OpenTelemetry.
Experience implementing SLI, SLO, and error budget frameworks.
Experience with Infrastructure as Code technologies such as Terraform or CloudFormation.
Cloud certifications within Azure, AWS, or Google Cloud.
Financial services experience preferred.
Experience supporting highly regulated enterprise environments.
Team & Environment
Works closely with Enterprise Architecture, Platform Engineering, Infrastructure, SRE, Security, and Application Development teams.
Serves as a key architecture resource supporting enterprise AI platform operations.
Participates in highly collaborative Agile teams.
Provides technical leadership supporting reliability and operational excellence initiatives.
Work Schedule & Travel
Schedule
  • Monday – Friday
  • Standard business hours
  • Flexible remote work environment
Travel
  • Occasional travel to Buffalo, NY
  • Approximately every 4–6 weeks as required
Compensation & Benefits
  • Competitive hourly compensation
  • Long-term contract engagement
  • Remote work flexibility
  • Opportunity to influence enterprise-wide AI strategy and adoption
Why Join This Opportunity?
This is a unique opportunity to help build and operate next-generation AI platforms at enterprise scale. The successful candidate will play a critical role in ensuring the reliability, resilience, observability, and operational success of AI technologies that support strategic business initiatives across the organization.