below marketmost similar roles pay hereabove market
This role pays less than
53%
of similar roles. Most pay
$193,075–$254,750
— the blue band above.
At the midpoint, this role pays about
$214k
versus about
$224k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3564 open roles
on FindRole.
Listed pay typically runs
$166,600–$277,600
across 2760 roles with salary data.
The Senior Applied AI Engineer joins the Data Insights team to build and advance AI-powered analytics and decision-support systems for Apple Ads. This role involves designing and evolving an AI agent platform that connects large language models with internal data infrastructure, analytical tools, and business knowledge to answer complex questions through natural language. Key responsibilities include agent orchestration, tool calling, memory, context retrieval, and developing reusable platform components. The engineer will build evaluation frameworks and monitoring systems to improve observability, accuracy, and reliability. Required skills include Python programming, software engineering fundamentals, and experience with LLM-powered applications using agentic workflows, RAG, and distributed data systems. The work focuses on transforming emerging AI technologies into practical tools to improve how teams access insights and make decisions.
Design and build scalable AI agent systems connecting LLMs with data infrastructure, APIs, and analytical tools.
Advance agent orchestration including tool calling, memory, context retrieval, and intelligent routing.
Develop reusable platform components to enable teams to build AI-powered analytical workflows.
Build evaluation frameworks and monitoring systems to improve agent observability, accuracy, and reliability.
Apply machine learning principles to improve retrieval quality, reasoning, and traceability of AI-generated insights.
Develop AI-native solutions from concept to production while optimizing for scalability, latency, and maintainability.
Translate domain expertise and analytical workflows into reusable AI capabilities for engineers and business stakeholders.
What we're looking for
7+ years of experience.
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 with strong Python programming 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.
Solid foundation in AI, machine learning, statistics, and software engineering principles.
Experience architecting and scaling production AI agent platforms, including multi-step orchestration, tool execution, memory, and context management (preferred).
Advanced degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field (preferred).
Python
LLMs
Agentic AI
RAG
Machine Learning
SQL
Model Fine-tuning
Inference Optimization
Embeddings
Production Engineering
Statistics
Data Infrastructure
Machine Learning
NLP
Deep Learning
Information Retrieval
Reinforcement Learning
Statistics
Optimization
Forecasting
Agile
Production Systems
Design of Experiments