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Apple

Software Engineer - Distributed Systems

Oct 2, 2026• Hyderabad, India

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Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

★ 3.7 out of 5 · 120 reviews

  • Size: 10,000+ employees
  • Industry: Technology: Manufacturing
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Why you should apply for a job to Apple:

  • Ranked as one of the Best Technology Companies in 2020
  • 3.7/5 in overall job satisfaction
  • 3.1/5 in supportive management
  • 66% say women are treated fairly and equally to men
  • 65% would recommend this company to other women
  • 66% say the CEO supports gender diversity

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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.","responsibilities":"Design, build, and operate low-latency backend services that participate in every ad request, with strict SLAs and fail-safe behavior
Own one or more Ad Delivery capability areas end-to-end - from service design and data contracts to production operations
Build near-real-time data pipelines that keep runtime services accurate: spend counters, policy rules, targeting attributes, and traffic-quality signals
Define and evolve service contracts with the adserver and adjacent platforms (auction, ranking, experimentation, retrieval)
Implement fail-closed semantics - when a signal is missing or stale, safely decline to serve and emit a structured reason code that flows through the downstream funnel
Contribute to a shared data-grid plane used by ad serving for local, region-replicated lookups
Build observability, debugging, and replay tooling so on-call engineers can quickly reason about eligibility, spend, and policy decisions
Participate in on-call rotations and lead incident response for production ad-delivery systems
Partner with engineers across Cupertino, Austin, and Hyderabad in a one-team model

Preferred Qualifications
Background in Advertising technology - ad serving, budget pacing, spend accounting, policy enforcement, fraud/traffic quality, or query understanding
Experience with near-real-time counter systems at scale
Experience with KV stores and region-replicated caches, and reasoning about staleness and consistency
Familiarity with information retrieval basics - query normalization, tokenization, stemming, spell correction, close/broad variants
Background in trust and safety, bot detection, or fraud prevention systems
Experience with offline enrichment pipelines (Spark, Flink, or equivalent) alongside runtime services
Track record of improving developer tooling, test coverage, and platform ergonomics in a large shared codebase

Minimum Qualifications
2-5 years of software engineering experience with a focus on backend or distributed systems
Strong programming skills in Java (Spring / Spring Boot), including concurrency and JVM performance
Hands-on experience building and operating high-throughput, low-latency services with sub-100 ms latency budgets
Solid understanding of service design fundamentals - REST/gRPC APIs, timeouts, retries, circuit breakers, backpressure, and graceful degradation
Experience with streaming data infrastructure such as Apache Kafka or equivalent
Familiarity with cloud platforms (AWS preferred), container orchestration, and CI/CD
Strong operational instincts - metrics, logging, alerting, and on-call ownership
Hands-on experience with using AI for development and/or building AI-based tools

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Additional Information

  • Posted: Oct 2, 2026
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