Apple
Site Reliability Engineer (Edge Services), Infrastructure Services
$135K–$278K
Austin, Texas +3 · Full-time · Posted May 18, 2026
- Location
- Austin, Texas
Denver, Colorado
Elk Grove, California
Sunnyvale, California - Education
- B.S. in Computer Science, Computer Engineering, or a related technical field, or equivalent professional work experience.
About the job
Build and operate reliable, observable edge services by developing monitoring and alerting, automation, and reliability practices for distributed systems.
What you'll do
- Design observability and alerting focused on high-cardinality data and actionable signals.
- Automate operations and build self-healing systems to reduce toil.
- Partner with development teams to integrate reliability into CI/CD and proactively address performance bottlenecks.
What they ask for
- B.S. in Computer Science, Computer Engineering, or a related technical field, or equivalent professional work experience.
- Understanding of Linux internals and deep networking expertise, including HTTP/2, HTTP/3 (QUIC), and HTTPS/TLS.
- Ability to automate tasks and workflows using Python or Go; experience with monitoring suites such as Prometheus, Grafana, or ClickHouse.
- Knowledge of Data Structures and Algorithms, SLIs, SLOs, Error Budgets, Release Management, and Incident Management.
Nice to have
- Cloud experience with AWS, GCP, or Azure and infrastructure tools such as Terraform, Ansible, or Pulumi; Kubernetes experience.
- Experience leading blameless post-mortems, consulting on service design, or applying Generative AI tools in SRE and software engineering workflows.
Pay
$134,700 and $249,500 (base salary); $150,400 and $277,600 (base salary)
Tools
Linux, HTTP/2, HTTP/3 (QUIC), HTTPS/TLS, Python, Go, Prometheus, Grafana
AI focus
Apply Generative AI to observability queries, alert design, AI-assisted debugging and triage, and repeatable context-aware workflows; validate and iterate on outputs in production-adjacent contexts.
Model-written summary · the original posting is authoritative