채용
필수 스킬
AWS
Excel
Join us on the Content Excellence team as a Content Strategist and help define the standards and frameworks that govern AWS technical content.
At AWS, content consistency doesn't happen by accident; it requires clear specifications for how content is structured, organized, evaluated, and managed. As AI transforms content creation and management, these foundational rules become essential for authors and machines alike.
As part of the Technical Content Experience organization, the Content Excellence team is looking for a strategic thinker to define what good content looks like, and then partner with platform teams, content creators, and AI systems to ensure those standards are understood, adopted, and applied. The right candidate thinks in frameworks and systems and influences through clarity and collaboration. They excel at translating ambiguity into actionable specifications that other teams operationalize.
This role requires exceptional communication skills, strong analytical thinking, and the ability to influence without authority.
Key job responsibilities
-Define the content ecosystem strategy that outlines what customer needs AWS content must serve, how properties should be organized, and what content should be single-sourced.
-Create content architecture standards. Define the categories, taxonomy, and organizational structures that enable unified and intelligent content management.
-Manage the content model. Specify content types, components, and metadata that authors and AI systems use as their foundation.
-Establish content patterns. Document assembly rules for each content type so anyone can create or generate compliant first drafts.
-Maintain the Content Design System as the single source of truth for how AWS content should be created and managed.
-Define quality criteria that distinguishes good content from bad, enabling data-driven evaluation and routing decisions.
-Specify content lifecycle stages, triggers, and evaluation criteria that enable proactive management at scale.
-Define gold-standard criteria for AI training corpus curation.
-Drive alignment across stakeholders on definitions, criteria, and specifications.
About the team
The Content Excellence team ensures every piece of AWS technical content delivers a predictable, high-quality experience aligned to customer needs and business outcomes. We define the standards that make this possible at scale: content ecosystem strategy, content architecture, content models, content patterns, quality definitions, governance criteria, lifecycle frameworks, AI training corpus criteria, and the Content Design System.
Basic Qualifications
- 3+ years of editor, content strategist, technical writer, or content developer experience
- Experience using data and metrics to determine and drive improvements
- Experience using content management systems and content tools
- Experience designing, planning, and delivering content solutions that meet the needs of technical business customers
- Experience building cross-functional partnerships and influencing stakeholders across the organization to act without having a direct reporting relationship
- Experience establishing governance frameworks or quality criteria for content at scale
Preferred Qualifications
- Experience building ontologies, taxonomies, and semantic relation frameworks
- Experience implementing change management successfully transitioning programs into large-scale operations
- Experience defining requirements for AI-assisted content systems
- Understanding of content lifecycle management frameworks
- Experience rationalizing or consolidating fragmented content ecosystems
- Experience documenting standards, patterns, or guidelines for broad organizational adoption
- Familiarity with structured content concepts (DITA, component content management, content reuse)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, VA, Arlington - 71,500.00 - 125,200.00 USD annually
USA, WA, Seattle - 80,200.00 - 125,200.00 USD annually
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Amazon 소개

Amazon
PublicAmazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.
10,001+
직원 수
Seattle
본사 위치
$1.5T
기업 가치
리뷰
2.9
10개 리뷰
워라밸
2.8
보상
3.7
문화
2.5
커리어
2.3
경영진
2.1
35%
친구에게 추천
장점
Good pay and compensation
Strong benefits package
Flexible scheduling options
단점
Poor management and leadership
Limited growth and promotion opportunities
High stress and demanding work environment
연봉 정보
2개 데이터
L2
L3
L4
L5
L6
L2 · Data Analyst L2
0개 리포트
$108,330
총 연봉
기본급
$43,332
주식
$54,165
보너스
$10,833
$75,831
$140,829
면접 경험
10개 면접
난이도
3.7
/ 5
소요 기간
21-35주
합격률
20%
경험
긍정 10%
보통 10%
부정 80%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Onsite/Virtual Loop
6
Team Matching
7
Offer
자주 나오는 질문
Coding/Algorithm
System Design
Behavioral/STAR
Leadership Principles
Technical Knowledge
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