below marketmost similar roles pay hereabove market
This role pays more than
95%
of similar roles. Most pay
$126,800–$211,510
— the blue band above.
At the midpoint, this role pays about
$255k
versus about
$169k
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
3497 open roles
on FindRole.
Listed pay typically runs
$174,149–$277,600
across 2702 roles with salary data.
The Applied AI & Data Engineer - Business & Education joins the team responsible for the infrastructure, platforms, and services powering enterprise and education offerings, including device management and subscription services. This role involves designing and building a data and AI platform on Databricks and AWS, owning agentic systems end-to-end, and developing RAG pipelines, vector search, and knowledge graphs. You will build natural-language data interfaces and intelligent workflows while managing model selection, latency, and token economics. Key technologies include LangChain, LlamaIndex, Spark, Kafka, Delta Lake, and SQL engines like Trino or Presto. You will use Python, Scala, Java, or Go to create production-ready systems that provide AI-accelerated pipeline development and self-serve analytics for data engineering and science teams within a complex, high-volume business environment.
Design and build data and AI platforms on Databricks and AWS using modern cloud-native patterns.
Own AI and agentic systems end-to-end, including retrieval, planning, evaluation, guardrails, and deployment.
Build RAG pipelines, vector search, knowledge graphs, and multi-agent orchestration for natural-language data interfaces.
Optimize systems for scale by managing model selection, latency, throughput, and token economics.
Translate ambiguous requirements from stakeholders into secure, scalable, and production-ready systems.
Provide technical leadership through design reviews, implementation guidance, and production-readiness checks.
Mentor engineers and develop technical playbooks to help the team adopt AI-native practices.
Research and implement state-of-the-art data and AI techniques to accelerate pipeline development and analytics.
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.
BS or MS in Computer Science, Information Systems, AI, Machine Learning, Engineering, Mathematics, Statistics, or a related field, or equivalent practical experience.
Hands-on fluency with LLM/agent frameworks, vector search, RAG pipelines, and multi-agent coordination.
Proficiency in at least one high-level language (Python, Scala, Java, or Go) and strong SQL.
Experience designing scalable data platforms on modern cloud-native patterns like Databricks and AWS.
Experience delivering ETL/ELT, streaming, and CDC pipelines using Spark, Kafka, and Delta Lake.
3+ years of experience mentoring engineers and providing hands-on technical leadership.
Model and prompt customization at scale, including fine-tuning and training reward models (preferred).
Experience with MLOps, LLMOps, and building natural-language interfaces over data (preferred).
Experience with Google Cloud, Azure, Apache Flink, or NoSQL datastores (preferred).
Experience building AI systems in regulated or privacy-sensitive environments (preferred).