AI Data & Infrastructure Engineer

Apple Inc

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Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 23 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $187k

This role $255k

$110k $348k

below market most similar roles pay here above market

This role pays more than 91% of similar roles. Most pay $142,500–$230,775 — the blue band above. At the midpoint, this role pays about $255k versus about $187k 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.

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At a glance

TL;DR · AI Data & Infrastructure Engineer

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The AI Data & Infrastructure Engineer joins the Manufacturing Systems and Infrastructure team to design, build, and operate scalable AI data systems powering enterprise GenAI and Agentic AI capabilities. This role involves developing data ingestion, transformation, and publishing pipelines for multimodal data while implementing Retrieval-Augmented Generation pipelines, embedding workflows, and vector database integrations. The engineer will build robust architectures for data orchestration, infrastructure provisioning, and manufacturing workflow automation. Key technologies include Python, SQL, Java, Scala, Spark, Kafka, Ray, Airflow, Kubeflow, and MLflow. Candidates must navigate cloud-native environments using Kubernetes, Docker, and Infrastructure as Code. The work focuses on solving complex manufacturing operations problems by creating observable, debuggable systems that optimize platform scalability, reliability, and performance for industrial data and agentic systems.

Skills

Python SQL Java Scala Spark PySpark Kafka Airflow Kubeflow MLflow Ray Pandas Kubernetes Docker AWS Azure GCP CI/CD RAG Vector Databases Iceberg Delta Lake

What you'll do

Design and build scalable AI data platforms, services, and APIs to support Agentic AI workflows.
Develop data ingestion, transformation, and publishing pipelines for structured, unstructured, and multimodal data.
Implement Retrieval-Augmented Generation (RAG) pipelines, embedding workflows, and vector database integrations.
Build and integrate tools to make complex AI systems observable, understandable, and debuggable.
Optimize platform scalability, reliability, performance, security, and cost across cloud-native environments.
Create robust architectures for systems that handle data orchestration for enterprise AI features.
Build and integrate tools to enable manufacturing workflow automation through Agents and Agent skills.

What we're looking for

Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
Experience designing and building scalable data platforms and distributed systems.
Strong programming skills in Python and SQL, with proficiency in Java or Scala (preferred).
Experience with Airflow, Kubeflow, or MLflow to build and orchestrate scalable AI data pipelines.
Experience building batch and streaming data pipelines using Spark (PySpark), Kafka, Airflow, and Ray, with proficiency in Pandas and modern data lake architectures.
Experience with cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and Infrastructure as Code.
Knowledge of RAG architectures, embedding generation, vector databases, and AI data preparation for LLMs and agentic AI.
Experience with Generative AI, LLMs, Agentic Systems, API design, or industrial data platforms (preferred).