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Manager, AI Platform Engineering , Agent Platform Organization
We are looking for a Manager of AI Platform Engineering to lead a team of AI platform engineers building and operating the data pipelines, models, and platform infrastructure that power core analytics, science and AI intatives. You will own the delivery and operational health of multiple business domains, build and mentor a high-performing team, and help evolve our self-service offerings from reactive dashboards to proactive agent driven approaches.
Your team will use AI development IDEs and generative AI tooling daily, and will build multi-agent solutions that automate common data engineering and BI tasks (e.g. pipeline generation, data quality enforcement, testing, and operational response). You will guide this evolution, helping your engineers develop fluency with agentic tooling while maintaining the data engineering fundamentals that everything depends on. You will also help your engineers develop and deploy agents, that solve common Analytics use cases around monitoring, anomaly detection, and insight generation.
You will also partner with business intelligence, applied science, and product teams to translate data needs into technical roadmaps, and contribute to shared platform infrastructure when the work calls for it.
Basic Qualifications
- 3+ years of engineering team management experience
- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience working with technical and product stakeholders to define requirements, prioritize features, and influence product roadmaps
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- 7+ years of working directly within data engineering or closely related teams, with hands-on contribution to data platform and pipeline delivery
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- 3+ years of designing or architecting data systems, including data modeling, pipeline patterns, reliability, and scaling strategies
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- 5+ years of experience building or leading development of data pipelines and cloud-native data infrastructure (e.g., data warehouses, data lakes, event-driven architectures, orchestration platforms)
Preferred Qualifications
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- Experience leading teams that use generative AI tools and AI development IDEs to accelerate engineering work
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- Familiarity with multi-agent solutions that automate workflows (e.g. pipeline generation, data quality, testing, operational response)
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- Familiarity with at least one agentic AI development IDE (e.g. Kiro, Cursor, Claude Code, Codex)
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- Experience building or overseeing shared data models, semantic layers, or data contracts
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- Familiarity with data governance, cataloging, or lineage tracking practices
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- Experience contributing to or overseeing shared platform infrastructure, developer tooling, or self-service data services
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- Familiarity with observability tooling for data pipelines and data platform operations
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. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.
CAN, ON, Toronto - 154,200.00 - 257,600.00 CAD annually
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关于Amazon

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+
员工数
Seattle
总部位置
$1.5T
企业估值
评价
10条评价
3.4
10条评价
工作生活平衡
2.5
薪酬
4.2
企业文化
3.0
职业发展
3.8
管理层
2.7
65%
推荐率
优点
Great benefits and competitive pay
Learning and advancement opportunities
Good teamwork and colleagues
缺点
High pressure and long hours
Poor work-life balance
Toxic work culture and management issues
薪资范围
4个数据点
L2
L6
L3
L4
L5
L2 · Data Analyst L2
0份报告
$108,330
年薪总额
基本工资
$43,332
股票
$54,165
奖金
$10,833
$75,831
$140,829
面试评价
6条评价
难度
4.0
/ 5
时长
21-35周
体验
正面 0%
中性 17%
负面 83%
面试流程
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Phone Screen
5
Technical Interview
6
Onsite/Virtual Interviews
常见问题
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
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