below marketmost similar roles pay hereabove market
This role pays more than
94%
of similar roles. Most pay
$145,000–$217,906
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$181k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
JOB TITLE: Software Engineer, Infrastructure Services (Cloud Network Fault Tolerance)
Joining the Infrastructure Services team within the Information Systems and Technology organization, you will develop systems to make a hyper-scale cloud network dramatically more fault-tolerant. You will design and build automated detection, diagnosis, and remediation layers that identify network anomalies and take corrective actions in real time with minimal human intervention. Your daily work involves building sensing and decision-making logic, creating simulation and chaos testing tools, and analyzing systemic weaknesses to eliminate failure patterns. You must apply deep knowledge of distributed systems, control theory, and graph algorithms to solve complex problems. Required skills include proficiency in Go, C++, Rust, or Python, alongside experience with fault-tolerant mechanisms like circuit breaking, load shedding, and distributed consensus algorithms such as Raft or Paxos.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Design and build automated systems to detect, diagnose, and remediate network faults in a hyperscale cloud environment.
Develop decision logic and safety mechanisms for automated corrective actions on live production infrastructure.
Analyze network failure patterns and design software solutions to eliminate or mitigate systemic weaknesses.
Build simulation, chaos testing, and fault-injection tooling to proactively identify infrastructure vulnerabilities.
Apply formal reasoning regarding distributed systems and control theory to build robust, production-grade software.
Translate academic research and industry innovations into practical, large-scale resilience systems.
Prototype and experiment rapidly by validating new ideas against real production data and failure scenarios.
What we're looking for
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
4 to 6+ years of professional software engineering experience designing, building, and operating production-grade distributed systems and backend infrastructure.
Deep foundation in computer science fundamentals, including distributed systems architecture, concurrency models, graph algorithms, and systems design.
Strong proficiency in at least one systems-level or high-performance language such as Go, C++, Rust, or Python.
Direct experience designing and building fault-tolerant mechanisms like automated self-healing, active remediation, circuit breaking, and load shedding.
Demonstrated ability to model complex failure domains, handle network partitions, and reason about system behavior under extreme load.
Practical experience with chaos engineering, fault injection, simulation-based testing, and stress testing in production or staging environments.
Track record of technical ownership, including authoring design documents, driving code reviews, and leading post-mortem root cause analyses.
Master’s or Ph.D. in Computer Science, Distributed Systems, Networking, or a related technical discipline (preferred).
Deep domain knowledge in cloud networking, SDN control planes, L3/L4 routing protocols, and Linux networking constructs (preferred).
Hands-on experience implementing distributed consensus algorithms (e.g., Raft or Paxos) and closed-loop control systems (preferred).
Experience architecting high-throughput telemetry pipelines and automated anomaly detection systems (preferred).
Proven ability to translate academic papers and industry research into production systems (preferred).
History of notable open-source contributions, technical publications, or patent filings in distributed networking (preferred).