Staff SRE Engineer: Scale, Reliability & AI Observability

General Motors; Austin (TX); Hybrid; USD 180.000 - 240.000; Vollzeit

Zusammenfassung

General Motors seeks a Staff Engineer to advance the reliability and scalability of its data platforms and Software-Defined Vehicle initiatives. You will design observable, fault-tolerant systems, and partner with SRE, data engineering, and product teams to improve operations.

You will own CI/CD pipelines, SRE practices, and AI-enabled workflows, while leading incident responses and cross-team reliability improvements in a hybrid, multi-cloud environment.

Qualifikationen

• 8+ years in SRE, DevOps, or systems engineering with leadership experience.
• Experience building cloud-native, high-scale production systems.
• Strong design and operational capabilities across reliability, performance, and security.

Aufgaben

• Lead design/implementation of scalable, observable infrastructure for vehicle telemetry, data ingestion, and platform operations.
• Drive production readiness across multiple teams with reliable deployment, observability, and runbooks.
• Design and improve CI/CD pipelines with GitOps, progressive delivery, and rollback practices.
• Collaborate with SRE, product, and application teams to define SLOs, SLIs, and monitoring standards.
• Lead incident response, on-call rotations, and post-incident reviews to prevent recurrence.

Kenntnisse

SRE leadership

Cloud-native systems

Observability patterns

Production readiness

Incident management

CI/CD pipelines

Python/Go/Java

AI/Llm practices

Communication

Ausbildung

BS / MS / PhD in computer science or engineering

Tools

Azure

AWS

GCP

OTEL

Kubernetes

Terraform

GitHub Actions

Argo CD

Jobbeschreibung

General Motors seeks a Staff Engineer to advance the reliability and scalability of its data platforms and Software-Defined Vehicle initiatives. You will design observable, fault-tolerant systems, and partner with SRE, data engineering, and product teams to improve operations.

You will own CI/CD pipelines, SRE practices, and AI-enabled workflows, while leading incident responses and cross-team reliability improvements in a hybrid, multi-cloud environment.