Applied AI Engineer, Apple Ads

Apple • Austin, TX

18h

About The Position

Apple Ads is seeking an Applied AI Engineer for its Data Insights organization. The role combines software engineering, machine learning, and agentic AI development to build reliable, scalable AI-powered analytics and decision-support systems for Apple Ads. The engineer will help develop a platform that connects large language models with internal data infrastructure, analytical tools, and business knowledge so teams can answer complex questions using natural language.

The work spans agent orchestration, context retrieval, evaluation, and production engineering. The engineer will create reusable capabilities that help teams build AI-powered analytical workflows, and will work with engineers, data scientists, and business partners to turn emerging AI technologies and domain expertise into practical tools that improve access to insights and decision-making. Solutions are expected to be designed for scalability, latency, and maintainability.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Machine Learning, Data Science, or a related field, or equivalent practical experience.
• Experience designing, building, and deploying production software systems.
• Strong Python programming skills and software engineering fundamentals.
• Hands-on experience building and deploying LLM-powered applications using agentic workflows, tool calling, RAG, or related techniques.
• Experience with large-scale data platforms or distributed data systems.
• A solid foundation in AI, machine learning, statistics, and software engineering principles.
• Strong problem-solving, communication, and cross-functional collaboration skills.

Nice To Haves

• Experience architecting and scaling production AI agent platforms, including multi-step orchestration, tool execution, memory, and context management.
• Experience developing LLM evaluation frameworks, regression benchmarks, and observability systems to improve agent reliability and reasoning quality.
• Experience with advanced retrieval techniques, embeddings, model fine-tuning, or inference optimization.
• Experience building natural-language-to-SQL systems, analytical agents, or AI-powered decision-support platforms.
• Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field.

Responsibilities

• Design and build scalable AI agent systems connecting LLMs with data infrastructure, APIs, and analytical tools.
• Advance agent orchestration, including tool calling, memory, MCPs, context retrieval, and intelligent routing.
• Develop reusable platform components that enable teams to build and extend AI-powered analytical workflows.
• Build evaluation frameworks and monitoring systems to improve agent observability, accuracy, reliability, and performance.
• Apply machine learning and analytical principles to define and improve online and offline metrics for retrieval quality, reasoning, accuracy, and traceability of AI-generated insights.
• Develop AI-native solutions from concept through production, optimizing for scalability, latency, and maintainability.
• Partner with engineers, data scientists, and business stakeholders to translate domain expertise and analytical workflows into reusable AI capabilities.

What This Job Offers

• Job Type: Full-time