This role pays more than
93%
of similar roles. Most pay
$126,800–$214,000
— the shaded band above.
At the midpoint, this role pays about
$255k
versus about
$170k
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
1984 open roles
on FindRole.
Listed pay typically runs
$175,000–$277,600
across 1590 roles with salary data.
Applied AI & Data Engineer - Business & Education joins the team responsible for the infrastructure, platforms, and services powering enterprise and education products. This role involves designing and building a data and AI platform using Databricks, AWS, and cloud-native patterns to support device management, identity, and subscription services. You will develop end-to-end agentic systems, RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration to create natural-language data interfaces and intelligent workflows. The role requires expertise in Python, Scala, Java, or Go, along with SQL, Spark, Kafka, and Delta Lake. You will manage model selection, evaluation harnesses, and guardrails while ensuring system efficiency regarding latency and token economics. This position solves the challenge of building an AI-first data organization to accelerate pipeline development, intelligent alerting, and automated analytics for internal and external stakeholders.
Design and build data and AI platforms using Databricks, AWS, and cloud-native architectures.
Develop end-to-end agentic systems including retrieval, planning, evaluation, guardrails, and deployment.
Build infrastructure for GenAI features like RAG pipelines, vector search, and knowledge graphs.
Optimize system performance regarding model selection, latency, throughput, and token economics at scale.
Translate ambiguous requirements from stakeholders into secure, production-ready data and AI systems.
Provide technical leadership through design reviews, implementation guidance, and project lifecycle management.
Mentor engineers and lead the adoption of AI-native practices through workshops and playbooks.
Research and implement state-of-the-art techniques to accelerate pipeline development and provide natural-language data access.
What we're looking for
8+ years of experience in data, analytics, software, or ML engineering.
3+ years of experience building and shipping Applied AI and agentic LLM systems in production.
Proficiency in at least one high-level language (Python, Scala, Java, or Go) and strong SQL skills.
Experience designing and building scalable data platforms on Databricks, AWS, or equivalent cloud-native platforms.
Expertise in ETL/ELT, streaming, and CDC pipelines using technologies like Spark, Kafka, and Delta Lake.
Proficiency with LLM frameworks (LangChain, LlamaIndex), vector search, RAG pipelines, and multi-agent coordination.
3+ years of experience mentoring engineers and providing technical leadership across concurrent initiatives.
BS or MS in Computer Science, Information Systems, AI, Machine Learning, Engineering, Mathematics, Statistics, or a related field (or equivalent experience).