Senior Software Engineer - Tools, Intelligent Automation & Developer Platforms

At Apple, we work every day to create products that enrich people's lives. The Apple Ads team builds privacy-focused advertising platforms that operate at massive scale across Apple Services.

We are seeking a Senior Software Engineer to build intelligent developer tools, internal engineering platforms, and AI-enabled automation systems that improve how Apple Ads engineers develop, validate, debug, and deliver software.

This hands-on role combines strong computer science fundamentals, scalable software development, and practical AI/LLM implementation to transform engineering workflows and improve productivity, reliability, and software quality across teams. Join the Business Integration Testing (BIT) team within Apple Ads, where we are transforming engineering workflows through intelligent automation and developer tooling. You will develop scalable engineering solutions that integrate AI into existing workflows, reduce manual effort, and enable teams to identify and resolve issues earlier in the development lifecycle.

In this role, you will:

• Build and maintain scalable internal developer tools, engineering platforms, and automation systems.
• Develop AI/LLM-enabled tools and agent-based workflows that accelerate debugging, streamline validation, and automate complex engineering processes.
• Create reusable integrations and self-service capabilities across backend services, APIs, and distributed systems.
• Own technical architecture and implementation, balancing scalability, reliability, performance, and maintainability.
• Partner with engineering teams to identify automation opportunities and deliver solutions that improve engineering efficiency and software quality.8+ years of hands-on software engineering experience building production systems, developer tools, or engineering platforms. Strong computer science fundamentals, including data structures, algorithms, software design, and problem-solving. Proficiency in Python or Java, with the ability to write clean, maintainable, and extensible code. Solid understanding of backend services, APIs, distributed systems, and scalable software architecture. Demonstrated hands-on experience designing and implementing AI/LLM-enabled software solutions, with the ability to explain technical approaches, implementation decisions, and limitations. Proven ability to independently own complex technical projects, articulate architectural tradeoffs, and deliver reliable solutions. Effective communication and collaboration skills across engineering teams.Familiarity with agent-based architectures, Model Context Protocol (MCP), or other AI-enabled automation approaches. Background building internal developer platforms, self-service tools, CI/CD infrastructure, or automation frameworks. Knowledge of software validation, debugging workflows, or shift-left quality engineering practices. Exposure to advertising technology or other large-scale, distributed platform environments. Track record of delivering engineering tools adopted across teams, with measurable improvements in efficiency, reliability, or software quality.