AI Data & Infrastructure Engineer - GenAI Platform

Apple Inc.; Sunnyvale, Northern (CA, KY); Hybrid; USD 185,000 - 325,000; Full time

Job summary

Apple Inc. in Sunnyvale, CA is seeking an AI Data & Infrastructure Engineer on the MSI team to design, build, and operate scalable AI data systems powering enterprise GenAI and agentic AI capabilities across global manufacturing sites.

You will lead data ingestion, retrieval-augmented generation pipelines, vector databases, and observable platforms, collaborating with AI/ML, software, and operations teams to deliver reliable, cost-aware solutions.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 8+ years 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 cloud platforms (AWS, Azure, or GCP), Kubernetes, Docker, CI/CD, and IaC.

Responsibilities

• Design robust, scalable data architectures for AI features and data orchestration.
• Build and maintain AI data platforms, services, and APIs for Agentic AI workflows.
• Develop data ingestion, transformation, and publishing pipelines for structured and unstructured data.
• Design and implement RAG pipelines, embedding workflows, and vector DB integrations.
• Collaborate with AI/ML engineers and domain teams to deliver production-grade data solutions.
• Optimize scalability, reliability, security, and cost across cloud-native environments.

Skills

Python

SQL

Java/Scala

Airflow

Spark

Kubernetes

Docker

Cloud Platforms

Communication

Education

Bachelor's or Master's in CS/Software/Data Eng

Tools

Airflow

Kubeflow

MLflow

Job description

Apple Inc. in Sunnyvale, CA is seeking an AI Data & Infrastructure Engineer on the MSI team to design, build, and operate scalable AI data systems powering enterprise GenAI and agentic AI capabilities across global manufacturing sites.

You will lead data ingestion, retrieval-augmented generation pipelines, vector databases, and observable platforms, collaborating with AI/ML, software, and operations teams to deliver reliable, cost-aware solutions.