Site Reliability Engineer, Apple Data Platform

Apple • Austin, TX

21h

About The Position

The Apple Data Platform Site Reliability Engineer operates and supports Apple’s large, multi-cloud platform for internal engineers building data and AI products. The role spans data processing, ML/AI services, and infrastructure, with a focus on production reliability, incident response, automation, and customer support. The engineer will operate the platform portfolio and develop subject-matter expertise in ML/AI platform services, including Ray training and serving, LangGraph agent deployments, RAG architectures, embeddings, and vector stores. The role supports infrastructure behind ML/AI products rather than building models.

The position offers ownership of a set of services and the opportunity to drive their reliability roadmap in alignment with broader team goals. It involves partnering with development teams across time zones to onboard services, design monitoring and alerting, and improve operational capacity through automation and self-healing tools. Internal customer support is provided through Slack, alongside participation in a rotating on-call schedule that includes occasional weekday and weekend coverage.

Requirements

• Bachelor’s degree in Computer Science, an engineering-related field, or equivalent related experience.
• At least 3 years in a Site Reliability Engineering, DevOps, or infrastructure-focused role.
• Proficiency in Python.
• Experience with Kubernetes and at least one major cloud provider, AWS or GCP.
• Exposure to operating or supporting ML pipelines, model-serving infrastructure, or LLM-based systems in production.
• Strong communication skills and composure under pressure during incidents.
• Solid grounding in SRE principles, with prior on-call or production-support experience.

Nice To Haves

• Working knowledge of Golang.
• Hands-on experience operating or supporting Ray training or serving, LangGraph or similar agent orchestration frameworks, RAG architectures, embeddings platforms, or vector store platforms.
• Familiarity with MCP-based tooling and ML lifecycle or dataset management systems.
• Experience with S3 and cloud storage and networking fundamentals.
• Familiarity with observability tooling such as Prometheus, Grafana, Splunk, and PagerDuty.
• Working knowledge of CI/CD pipelines and deployment workflows.
• Deep understanding of one or more big data technologies, such as Spark, Flink, Airflow, Trino, or Notebooks.
• Track record of automating manual operations through scripting or tooling.
• Intellectual curiosity and a drive to keep learning.

Responsibilities

• Operate, monitor, and triage production and non-production environments across data processing, ML/AI, and multi-cloud infrastructure.
• Participate in a rotating on-call schedule across supported services, including occasional weekday and weekend coverage.
• Own the operational health of ML/AI platform services as a subject-matter expert, providing reliability support and customer guidance for Ray, LangGraph agents, RAG pipelines, embeddings, and vector store platforms.
• Provide Slack-based support to internal customers; screen, triage, and resolve service-related issues.
• Partner with development teams across time zones to onboard services, understand their architecture, and design monitoring, alerting, and dashboards.
• Build automation and self-healing tooling to reduce manual toil and scale operational capacity.
• Identify, escalate, and resolve production issues to protect platform reliability and customer experience.
• Collaborate with SRE and development partner teams, engineering, and program management to align execution with team and organizational goals.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level