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软件开发工程师,履约计划与执行

雇主

Amazon Data Services, Inc.

地点

远程 · Seattle · 美国

待遇

$面议

工作模式

远程

截止日期

1月17日

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岗位摘要

Design and build large-scale distributed systems for AWS infrastructure fulfillment planning and exe

岗位职责

AWS Infrastructure Servicesowns the design, planning, delivery, and operation of all AWS global infrastructure.
In other words, we're the people who keep the cloud running.
We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on.
We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.
You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles.
You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers.
And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Our team is at the heart of AWS compute fulfillment — we build the mission-critical systems that translate demand from major AWS services (EC2, S3, EBS, Networking, and more) into actionable plans for material procurement, data center capacity allocation, rack building, and rack landing across AWS's global infrastructure.
We are looking for a proven Software Development Engineer who thrives in a fast-paced, high-ambiguity environment and can hit the ground running.
You will own and build systems that are responsible for:
- Rack Building & Rack Landing — orchestrating the end-to-end lifecycle from plan to physical delivery
- Plan-to-Execution Convergence — proactively identifying deviations between planned and actual execution, surfacing root causes, and driving corrective actions
- Fulfillment Explainability — building intelligent systems that explain "why" plans miss targets, enabling planners and operators to take timely, informed action These are high-impact, globally-scoped systems where reliability and accuracy directly affect AWS's ability to meet customer demand.
You will work on challenging distributed systems problems at massive scale, leveraging modern AWS-native architectures.
Key job responsibilities
1. Design, build, and operate large-scale distributed systems that power AWS infrastructure fulfillment planning and execution.
2. Architect solutions that detect and explain deviations between build plans and execution outcomes, enabling proactive intervention.
3. Write high-quality, modular, testable code and set the standard for engineering excellence on the team.
4. Solve complex architecture and business problems with extensible, scalable solutions built on native AWS services.
5. Formally mentor engineers on design, coding, operational excellence, and troubleshooting.
6. Collaborate cross-functionally with demand planning, supply chain operations, and partner engineering teams in a global environment. About the team
The Fulfillment Planning and Execution team within Infrastructure Supply Chain Automation builds intelligent systems that plan and execute to AWS global compute need and provide visibility, explainability, and actionable insights across AWS's fulfillment supply chain.
We handle compute needs from every major internal AWS department — our systems are mission-critical and operate at global scale.
We are a fast-moving team that values ownership, bias for action, and delivering results that directly impact AWS's ability to scale for customers worldwide.

申请条件

Proven experience as a Software Development Engineer.
Ability to thrive in a fast-paced, high-ambiguity environment and hit the ground running.
Experience designing, building, and operating large-scale distributed systems.
Strong coding skills with high-quality, modular, testable code.

雇主简介

Amazon Data Services, Inc. 是亚马逊旗下负责数据中心基础设施的子公司,主要支持AWS云服务的数据中心设计、建设和部署。

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数据来源:Amazon

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