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Apple Software Engineer - Apple Ads United States, West Virginia 608852858
05.09.2025
- Tooling & Automation: Architect and develop internal AI-driven tools for observability, triage, and debugging, enabling support and engineering teams across Apple Ads.
- Proactive Diagnostics: Design solutions that automate complex investigations and detect anomalies before they impact customers.
- Collaboration & Adoption: Partner with business operations and engineering stakeholders to gather requirements, ensure adoption, and drive tool effectiveness.
- Engineering Excellence: Write clean, maintainable code with clear documentation, while mentoring teammates through code reviews and lightweight tooling guidance.
- Strategy & Roadmap: Contribute to the long-term tooling strategy, shaping the roadmap for support automation and scale.
- Issue Investigation: Conduct in-depth investigations of customer-reported issues, resolving them directly where possible and providing detailed findings to Engineering when code changes are required.
- Incident Management: Lead and facilitate incident calls, driving timely resolution to minimize downtime and end-user impact.
- Monitoring & Alerts: Configure and fine-tune observability tools (e.g., Splunk, Grafana) to proactively identify and address performance or availability concerns.
- Documentation: Create and maintain comprehensive SOPs, runbooks, playbooks, troubleshooting guides, and knowledge base articles.
- On-Call Coverage: Participate in rotational on-call duties to address critical production issues. Also handle service requests such as user access management, configuration updates, and related tasks.
- 5-8 years of software engineering experience, with a focus on designing and building internal tools.
- Proficiency in Java or Python, with strong systems-thinking skills and an emphasis on reliability.
- Demonstrated experience developing tools for support, observability, triage, or production diagnostics.
- Hands-on familiarity with logging and monitoring platforms such as Splunk, Datadog, or similar technologies.
- Proven ability to collaborate effectively across functions and communicate with both technical and non-technical stakeholders.
- Strong written communication skills with a commitment to producing clear, accurate documentation.
- Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
- Background in technical support, quality engineering, DevOps, or production operations.
- Experience with AI/ML-powered tooling, particularly in internal software workflows.
- Hands-on knowledge of AWS, Kubernetes, containerized deployments, or CI/CD environments.
- Familiarity with mobile advertising platforms, ad tech APIs, or developer-facing systems.
- Proven ability to mentor peers, influence technical roadmaps, and lead internal initiatives.
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