Senior AI Data & Infrastructure Architect

JobCubby; Sunnyvale, Northern (CA, KY); Hybrid; USD 180,000 - 240,000; Full time

Job summary

Apple seeks an AI Data & Infrastructure Engineer to lead end-to-end design, build, and operation of scalable AI data systems powering GenAI and Agentic AI for manufacturing operations.

You will design data pipelines, implement RAG architectures, and collaborate across teams to deliver production-ready solutions, with emphasis on scalable, observable systems and strong cross-functional collaboration.

Qualifications

• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field.
• 8+ years of experience designing and building scalable data platforms and distributed systems.
• Strong programming skills in Python and SQL; Java or Scala preferred.

Responsibilities

• Design robust, scalable architectures for AI data systems feeding GenAI and Agentic AI workflows.
• Build and maintain AI data platforms, services, and APIs supporting agentic AI.
• Develop data ingestion, transformation, and publishing pipelines for structured and unstructured data.
• Implement Retrieval-Augmented Generation (RAG) pipelines and embedding workflows.
• Collaborate with AI/ML engineers and product teams to deliver production-ready data solutions.
• Ensure observability, reliability, and cost efficiency across cloud-native environments.

Skills

Python

SQL

Spark

Kafka

Airflow

Kubeflow

MLflow

PySpark

Pandas

Iceberg

Delta Lake

Ray

Java/Scala

Kubernetes

Docker

CI/CD

Infrastructure as Code

Cloud platforms (AWS/Azure/GCP)

Education

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

Tools

Airflow

Kubeflow

MLflow

Spark (PySpark)

Kafka

Job description

Apple seeks an AI Data & Infrastructure Engineer to lead end-to-end design, build, and operation of scalable AI data systems powering GenAI and Agentic AI for manufacturing operations.

You will design data pipelines, implement RAG architectures, and collaborate across teams to deliver production-ready solutions, with emphasis on scalable, observable systems and strong cross-functional collaboration.