GenAI Data Platform & Infra Engineer

Apple, Inc.; Sunnyvale (CA); On-site; USD 185,000 - 325,000; Full time

Benefits offered by this job

Medical and dental coverage

Employee stock programs

Relocation assistance

Tuition reimbursement

Job summary

Apple in Sunnyvale is seeking an AI Data & Infrastructure Engineer to design, build, and operate scalable data systems powering enterprise GenAI capabilities. You will own end-to-end data platforms, pipelines, and RAG workflows enabling Agents and agentic AI across manufacturing.

The role collaborates with AI/ML engineers, software engineers, and domain experts to optimize scalability, reliability, security, and cost in cloud-native environments.

Qualifications

• Bachelor's or Master's in CS/Engineering/Data Engineering or related field.
• 8+ years designing and building scalable data platforms and distributed systems.
• Strong programming in Python and SQL; Java or Scala preferred.
• Experience with Airflow, Kubeflow, MLflow to orchestrate data pipelines.
• Experience with Spark, Kafka, Iceberg/Delta Lake, Pandas.

Responsibilities

• Create robust, scalable architectures for data orchestration for AI features.
• Design, build, and maintain scalable AI data platforms, services, and APIs.
• Develop ingestion, transformation, and publishing pipelines for structured and unstructured data.
• Design and implement Retrieval-Augmented Generation (RAG) pipelines and embeddings workflows.
• Collaborate with AI/ML engineers and product teams to deliver production-ready data solutions.

Skills

Python

SQL

Java

Scala

Education

Bachelor's degree in Computer Science/Engineering/Data Engineering

Tools

Airflow

Kubeflow

MLflow

Spark (PySpark)

Kafka

Pandas

Iceberg

Delta Lake

Kubernetes

Docker

CI/CD

Infrastructure as Code

Job description

Apple in Sunnyvale is seeking an AI Data & Infrastructure Engineer to design, build, and operate scalable data systems powering enterprise GenAI capabilities. You will own end-to-end data platforms, pipelines, and RAG workflows enabling Agents and agentic AI across manufacturing.

The role collaborates with AI/ML engineers, software engineers, and domain experts to optimize scalability, reliability, security, and cost in cloud-native environments.