below marketmost similar roles pay hereabove market
This role pays more than
95%
of similar roles. Most pay
$149,500–$206,450
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$178k
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
3564 open roles
on FindRole.
Listed pay typically runs
$166,600–$277,600
across 2760 roles with salary data.
The Senior Software Engineer — Service Observability & Detection joins the Service Observability & Detection team within Wallet, Payments, and Commerce. In this role, you will design and build telemetry foundations, SLO frameworks, and detection systems to provide real-time visibility into high-scale services. You will develop scalable telemetry pipelines, define instrumentation standards, and architect multi-tier SLO models to ensure reliability for payment and commerce platforms. Key responsibilities include building intelligent alerting systems, managing observability-as-code infrastructure, and solving complex problems like tail-based sampling and high-cardinality metric management. You will utilize OpenTelemetry, Kotlin, Java, Go, or Python, while leveraging platforms like Datadog, Grafana, Prometheus, or Splunk. This position addresses the critical need for high-availability, low-latency monitoring across distributed microservices and third-party integrations in a high-compliance financial environment.
What does a Software Engineer earn in California?
Median $214500 from 1156 postings across 72 companies.
Design and build scalable telemetry pipelines using OpenTelemetry for high-throughput, low-latency environments.
Define and enforce organization-wide telemetry standards for metrics, spans, and context propagation.
Architect multi-tier SLO frameworks including SLI definitions, error budget policies, and burn-rate alerting.
Build intelligent, multi-layered alerting systems to prevent alert storms and provide root cause attribution.
Implement end-to-end user journey monitoring by correlating traces, metrics, and logs across microservices.
Manage observability-as-code infrastructure through version-controlled, templatized deployment pipelines.
Develop automation tools for instrumentation gap detection and self-service onboarding for engineering teams.
Solve complex telemetry problems like tail-based sampling, high-cardinality management, and cross-service trace stitching.
What we're looking for
8+ years of experience in software engineering with deep expertise in observability, reliability engineering, or telemetry platform development.
Proven track record of leading cross-functional technical initiatives and driving adoption across multiple engineering teams without direct management authority.
Experience building telemetry and observability systems from the ground up, including designing instrumentation strategies, pipelines, and data models.
Deep hands-on experience with OpenTelemetry, including SDK instrumentation, Collector architecture, processors, exporters, and context propagation.
Strong understanding of SLOs, SLIs, and error budgets with experience defining and operating SLO-based alerting in production.
Experience designing alerting architectures for complex distributed systems, including burn-rate alerts and alert storm prevention.
Strong proficiency in at least two of the following languages: Kotlin, Java, Go, or Python.
Experience with observability platforms such as Datadog, Grafana, Prometheus, or Splunk.
Deep understanding of distributed systems concepts including microservices, API gateways, and event-driven systems.
Experience solving hard telemetry problems at scale, such as sampling strategies, high-cardinality metric management, and trace stitching.
Strong communication skills to translate complex technical observability concepts into clear strategies for engineering leadership.
BS or MS in Computer Science, Software Engineering, or a related field, or equivalent professional experience.
Experience working on payment systems, financial services platforms, or other high-compliance, high-availability domains (preferred).
Experience building observability platforms or telemetry infrastructure that serves an entire engineering organization (preferred).
Experience applying AI/ML to operational problems such as anomaly detection or automated incident correlation (preferred).
Experience with Infrastructure-as-Code tools such as Terraform or Pulumi for managing observability resources (preferred).