AnthropicSan Francisco, CA | Washington, DC$265k-$295kjust now
AmazonPosted 1w ago
Software Development Manager, AWS Payments & Fraud Prevention at Amazon scores 35 out of 100 on AI centrality, which makes it AI Level 1 of 4 (Little AI) on this board. The level measures how much of the work is AI, not seniority.
AI in this role
Lead a software development team building large-scale data ingestion and fraud detection systems for AWS payments.
You'll be leading the data ingestion and intelligence team that design and build systems that process millions of events per second, develop machine learning-powered fraud detection processes, and directly contribute to keeping AWS safe. Whether it's architecting a new real-time detection engine, optimizing our graph-based fraud network analysis, or hardening our registration fraud defenses — your work will have immediate, measurable impact at AWS scale.
Key job responsibilities
* Own and operate a large-scale data ingestion platform processing 18+ billion events per day, ensuring data is ingested, enriched, and transformed in near real-time to power fraud detection and prevention across the organization.
* Lead the design, development, and maintenance of real-time intelligence pipelines using Apache Flink for data aggregation, anomaly detection, and usage pattern analysis.
* Drive the development of a graph database of millions of nodes and edges to model account relationships and surface fraud signals.
* Ensure high availability, reliability, and scalability of all platform services, including data vending APIs operating at 4,500+ TPS, as business demands and the AWS customer base grow.
* Own day-to-day team operations, including sprint planning, technical design reviews, operational excellence, and on-call management.
* Plan and execute the team's multi-year technical strategy, aligning platform capabilities with evolving business and security needs.
* Collaborate closely with Applied Scientists to identify and deliver the data products they need to detect and prevent fraud and account compromise faster.
* Serve as a technical leader with hands-on depth, diving deep with SDEs to review architectures, and resolve platform issues.
* Ensure platform services meet the needs of all downstream engineering and data science teams across the organization who depend on this team's products.
About the team
The AWS Payments & Fraud Prevention team protects AWS and its customers from fraud, abuse, and account compromise at global scale. We build highly scalable, real-time systems that ingest billions of signals daily, process petabytes of data, and make split-second decisions to stop bad actors — from account registration through the entire customer lifecycle. Our stack includes Apache Flink for stream processing, AWS Neptune for graph-based intelligence, and machine learning models for adaptive detection. We're a team of builders who care deeply about customer trust and love solving complex problems at massive scale.
Basic qualifications
- 3+ years of engineering team management experience
- 7+ years of working directly within engineering teams experience
- 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- 8+ years of leading the definition and development of multi tier web services 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 partnering with product or program management teams
Preferred qualifications
- Experience in communicating with users, other technical teams, and senior leadership to collect requirements, describe software product features, technical designs, and product strategy
- Experience in recruiting, hiring, mentoring/coaching and managing teams of Software Engineers to improve their skills, and make them more effective, product software engineers
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, WA, Seattle - 184,900.00 - 250,200.00 USD annually
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Skills and AI tools this role asks for
Questions you could be asked
- Tell me about a project where software development management was part of your work. What did you do?
- Tell me about a project where fraud prevention was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where big data was part of your work. What did you do?
- Tell me about a project where real time analytics was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Software Development Management, Fraud Prevention, Distributed Systems, Big Data, and Real Time Analytics. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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