Senior Cloud Infrastructure and AI Efficiency Engineer

Apple Inc

Confirmed live today High trust

Quick summary

Work type
On-site
Location
—
Salary
$184,700–$324,800 / yr
Posted
1 day ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $183k
This role $255k
$116k most similar roles pay here $347k

This role pays more than 92% of similar roles. Most pay $144,350–$222,250 — the shaded band above. At the midpoint, this role pays about $255k versus about $183k 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 3513 open roles on FindRole.

Listed pay typically runs $165,800–$277,600 across 2730 roles with salary data.

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At a glance

TL;DR · Senior Cloud Infrastructure and AI Efficiency Engineer

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The Senior Cloud Infrastructure and AI Efficiency Engineer joins the Cloud Infrastructure Business Operations team to drive data-driven insights regarding infrastructure planning, strategy, and delivery. This role involves building insights into cloud services such as architecture, cost, and utilization across hybrid and multi-cloud environments, including private clouds and public providers for compute, storage, and AI training clusters. The engineer will translate high-dimensional infrastructure data into business metrics to provide strategic recommendations for financial and operational value. Key responsibilities include using AI to deliver proactive insights and managing large-scale systems while ensuring user privacy. Required skills include SQL, container orchestration with Docker and Kubernetes, and experience with FinOps tools like Cloudability or CloudHealth. The role addresses the challenge of optimizing infrastructure at scale by leveraging foundation models, agentic AI, and LLM-powered workflows to improve architectural decisions.

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