Cloud Infrastructure and AI Efficiency Engineer

The people here at Apple don’t just create products—they create the kind of

wonder that’s revolutionized entire industries. We know our ability to continue

creating the world’s most innovative products depends on people who represent

the variety of the human experience and who inspire us with great thinking.

Because the broader the backgrounds and perspectives, the bigger the ideas.

DESCRIPTION

Join the Cloud Infrastructure Business Operations team that is transforming the

way Apple plans, strategizes and delivers its cloud resources, data centers, and

hardware. We are seeking an experienced engineers to drive data and insights on

planning the strategy for Apple’s infrastructure. We partner with engineering,

finance, procurement and other supply chain teams to align engineering

strategies.

MINIMUM QUALIFICATIONS

5+ years in an engineering role — with a track record of owning and delivering

complex initiatives end-to-end. Able to research, architect and drive complex

technical solutions, consisting of multiple technologies, cloud services and AI

systems — from early prototype to production at scale. Able to write SQL

hands-on with AI, understand schema design, and recognize what makes queries

expensive. Knows enough to ask data engineers the right questions, not just the

broad ones. Experience with compute containerization and orchestration

technologies (e.g., Docker, Kubernetes) for pod-based service deployment,

operations and lifecycle management. Genuinely curious about AI — actively

explores new tools and workflows, brings ideas about what the team should adopt

next, and knows how to translate those ideas into concrete asks for platform

teams to build or support. Curiosity about GPUs, AI/ML systems and LLM-powered

workflows — actively explores new tools and workflows, brings ideas about what

the team should adopt next, and knows how to translate those ideas into concrete

asks for platform teams to build and support. Ability to define architecture by

influencing the cross-functional and software development team, while partnering

with business to ensure their strategic vision with software technology is met.

PREFERRED QUALIFICATIONS

Bachelor's Degree in Computer Science, Engineering, or a related discipline, or

equivalent practical experience. We value what you can do, not just where you

studied. The mindset and ability to work with large data and understand the

observability and statistics space specifically. Believes the rules of cloud

efficiency are being rewritten — has experience with foundation models, agentic

AI, and AI-native workflows, and inspired about how they change the way

infrastructure is architected, measured, and optimized. Stays close to the

frontier, brings ideas back to the team, and shapes how Apple gets ahead of the

shift rather than reacts to it. 5+ years designing, operating, and optimizing

infrastructure across public and private cloud environments (AWS, GCP, or

equivalent on-premise), with a strong intuition for how architectural decisions

translate into cost and performance outcomes at scale. Experience in cloud

platforms (AWS, GCP, Azure) — including security, cost optimization, and

governance best practices across hybrid and multi-cloud environments. Experience

designing and deploying scalable, cloud-native architectures with a strong

foundation in distributed systems, reliability, and fault-tolerant design.

Hands-on experience with FinOps and cost optimization — using tools like

Cloudability or CloudHealth, and applying AI-assisted analysis to surface

savings opportunities, model tradeoffs, and drive accountability across

engineering teams. Strong analytical foundation — proficient in trending,

variance analysis, and forecasting, with the ability to build and communicate

AI-augmented models that inform capacity planning and financial strategy. Deep

familiarity with Kubernetes — including optimization strategies for resource

efficiency, bin packing, autoscaling, and cost-aware scheduling in multi-tenant

and dedicated cluster environments. Experience with cloud observability and

telemetry tooling (e.g. CloudWatch, Datadog, Honeycomb) — able to connect

signals from infrastructure health, performance, and cost into a coherent

operational picture. Experience building Finance or FinOps subject areas from

the ground up — including unit economics, chargeback models, and the data

pipelines and taxonomies that make cost attribution meaningful at scale. Clear,

compelling communicator — able to translate complex technical and financial

narratives into crisp insights for both engineering and executive audiences, in

writing and in the room. Informed perspective on the AI landscape — follows the

evolution of foundation models, emerging tooling, and industry adoption patterns

closely enough to help shape how Apple prioritizes and invests in AI

capabilities across its cloud infrastructure.