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Senior DevOps EngineerSDI International • Chicago, Illinois, United States
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Senior DevOps Engineer

SDI International
  • US
    Chicago, Illinois, United States
  • US
    Chicago, Illinois, United States
Jetzt Bewerben

Über

No H1 or C2C. Must be Permanent Resident or US CitizenSenior DevOps Platform EngineerDescription and RequirementsAbout Our TeamWe are building Quantum, a next-generation hybrid AI platform that spans Windows, Android, and cloud. As part of this vision, we are expanding the engineering organization supporting cross-device Personal AI. We are hiring Senior DevOps / Platform Engineers to build and operate the core automation, infrastructure, and service platforms that enable secure, reliable, and high-velocity delivery of AI systems across device, edge, and cloud.
Depending on your background, you may be aligned to Platform Engineering, Observability, Operations, or Service Reliability—based on experience and organizational need. Operates with the speed, ownership, and creativity of a startup, supported by the scale, resources, and technical depth. We are building foundational systems from the ground up—intentionally, pragmatically, and with a culture of engineering excellence. Location: Open to remote work in the US. The preferred work location is Chicago, IL.What You Might Work OnAs a Senior DevOps / Platform Engineer, you may be responsible for a subset of the following areas depending on team placement: CI/CD, Automation & ToolingDesigning, implementing, and improving CI/CD pipelines for AI, platform, and application teams. Building automation and developer tooling to improve productivity and consistency. Developing infrastructure-as-code for cloud and hybrid environments (Terraform, Bicep, etc.). Platform & Infrastructure EngineeringImplementing scalable, secure, and resilient infrastructure on Azure and Kubernetes. Building and operating hybrid systems spanning device, edge, and cloud computeEnabling reliable platform services that support inference, data pipelines, and high-performance AI workloads. Observability & TelemetryImplementing and enhancing observability systems using OpenTelemetryGrafana, Prometheus, Loki, and related tooling. Ensuring platform telemetry is accurate, actionable, and tied to performance and reliability outcomes. Building dashboards and analytics for service health and operational insight. Deployment & Release EngineeringImproving deployment workflows, safety, consistency, and traceability. Supporting progressive delivery patterns including canaries, staged rollouts, and automated rollbacks. Optimizing CI/CD and deployment tooling for hybrid AI services. Collaboration & Reliability CulturePartnering closely with SRE, AI/ML, security, firmware, and product engineering teams. Contributing to system design discussions with a focus on automation, scalability, and operational best practices. Helping define and evolve platform engineering standards, patterns, and conventions. Basic Qualifications10+ years in DevOps, Platform Engineering, Cloud Engineering, or related fields Bachelor's Degree in Computer Science, Engineering, or a related technical field Strong experience building and operating infrastructure in Azure, AWS, or GCP Proficiency with CI/CD systems, build automation, and deployment pipelines Experience with Infrastructure as Code (Terraform, ARM/Bicep, CloudFormation, etc.) Strong development or scripting skills (Python, Go, Bash, or similar) Hands-on experience with Docker and KubernetesUnderstanding of observability fundamentals (metrics, logs, tracing) Preferred QualificationsDeep experience with Azure cloud architecture and DevOps tooling Strong hands-on work with OpenTelemetry (instrumentation, pipelines) Experience with Grafana, Prometheus, Loki, Tempo, or similar observability tools Experience supporting AI/ML workloads or GPU-accelerated compute environments Familiarity with event-driven systems and operationalizing data pipelines Experience contributing to or running on-call rotations Passion for automation, developer experience, and infrastructure reliability at scale What Success Looks LikeCI/CD pipelines are fast, stable, and trusted. Platform infrastructure becomes more automated, observable, and scalable. Telemetry and dashboards provide clear visibility into system health. Deployments are consistent, safe, and repeatable. Engineering teams move faster thanks to strong platform foundations. Hybrid AI platform becomes increasingly reliable, efficient, and easy to operate.
  • Chicago, Illinois, United States

Sprachkenntnisse

  • English
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