Summary
Apple Ads helps developers and businesses reach customers on the App Store through highly relevant, privacy-focused advertising. Our engineering teams build the infrastructure that powers ad delivery at Apple scale — from search and retrieval to auction, ranking, and measurement.
Description
We are looking for a Software Engineer to join the team responsible for Apple Ads' Ad Delivery Services — the runtime and offline systems that decide, for every ad request, which candidates are eligible, safe, and available to serve. Ad Delivery Services sit on the critical path of every impression Apple Ads serves. The team owns capability areas across Budget & Spend, Ad Delivery Policy, Traffic Quality, Request & Query Understanding, and Targeting Enrichment. Each capability is a low-latency service called inline during ad serving, plus the offline pipelines that keep it accurate. You will design and operate services that handle high request volumes with tight latency budgets, evolve them to support new ad placements and product surfaces, and partner closely with adserver, auction, ML, and data platform teams across Apple Ads.
Minimum Qualifications
- 2-5 years of software engineering experience with a focus on backend or distributed systems
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Strong programming skills in Java (Spring / Spring Boot), including concurrency and JVM performance
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Hands-on experience building and operating high-throughput, low-latency services with sub-100 ms latency budgets
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Solid understanding of service design fundamentals — REST/gRPC APIs, timeouts, retries, circuit breakers, backpressure, and graceful degradation
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Experience with streaming data infrastructure such as Apache Kafka or equivalent
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Familiarity with cloud platforms (AWS preferred), container orchestration, and CI/CD
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Strong operational instincts — metrics, logging, alerting, and on-call ownership
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Hands-on experience with using AI for development and/or building AI-based tools
Preferred Qualifications
- Background in Advertising technology — ad serving, budget pacing, spend accounting, policy enforcement, fraud/traffic quality, or query understanding
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Experience with near-real-time counter systems at scale
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Experience with KV stores and region-replicated caches, and reasoning about staleness and consistency
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Familiarity with information retrieval basics — query normalization, tokenization, stemming, spell correction, close/broad variants
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Background in trust and safety, bot detection, or fraud prevention systems
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Experience with offline enrichment pipelines (Spark, Flink, or equivalent) alongside runtime services
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Track record of improving developer tooling, test coverage, and platform ergonomics in a large shared codebase
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