June 12, 2022
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Remote, United States
June 12, 2022
Apply NowJob description
In this role, you will be a technical expert with significant scope and impact. You will work closely with a group of Software Development Engineers, Product Managers, Data Scientists, and Business Intelligence Engineers to create the data infrastructure and pipelines necessary to drive our team’s initiatives.
Job summary
In the AWS WAF Intelligence team, we build advanced bot control software that gives customers visibility and control over pervasive bot traffic that can consume excess resources, cause downtime, or perform other undesired fraudulent activities. We make it easy for customers to detect fraud and to help protect their web applications from attacks by analyzing large volumes of data in real-time for modeling suspicious behavior through machine learning and fingerprinting techniques. By supporting association with CloudFront, Application Load Balancer, API Gateway and AppSync customers can protect their applications and resources whether all in on the Cloud, maintaining on premise data centers, or using a hybrid Cloud approach.
We build a highly available low latency distributed system that allows customers to propagate changes worldwide in minutes to respond to active attacks in real-time. Using AWS Firehose, customers can store their full WAF logs for compliance and auditing as well as use them for debugging and additional forensics. We support using AWS Config to track historical changes to the rules and metrics associated with their WAF RuleGroups. Using CloudFormation customers can automate the deployment of their WAF Security Automations on the AWS Cloud.
You will play a lead role on the team and influence how we design, develop, build, deploy and support AWS WAF. To be successful in the role, you must be able to research, innovate and create unique solutions. There is no precedent to follow in this problem space. You will be involved from inception to deployment and beyond. You’ll interact with our customers, gathering requirements, designing, implementing, testing and supporting the product operationally; soup to nuts. You will be expected to use your technical background and have a significant impact on the direction of AWS WAF as well as new services that we develop in the future.
We own the direct customer experience as well as the per request processing of rules for CloudFront, API Gateway, and ALB. Not only do we build an AWS Security service, but we’re a customer of AWS using other AWS services to provide the solutions to our customers that scale and seamlessly integrate with their existing workflows. Engineers on our team get to solve some of the hardest computer science problems including building highly available distributed micro-services, global scaling across both AWS Regions and CloudFront edge locations, and processing millions of requests with single digit millisecond latency.
For employees based in Colorado, the base pay range for this position is $143,700.00 to 194,400 to USD per year; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on payment and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site. - https://www.amazon.jobs/en/landing_pages/benefitsoverview-us https://www.amazon.jobs/en/landing_pages/pto-overview-us
Successful candidates must have a big data engineering background with hands-on
experience in putting experimental machine learning models into production-standard data pipelines:
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.
Job summary
In the AWS WAF Intelligence team, we build advanced bot control software that gives customers visibility and control over pervasive bot traffic that can consume excess resources, cause downtime, or perform other undesired fraudulent activities. We make it easy for customers to detect fraud and to help protect their web applications from attacks by analyzing large volumes of data in real-time for modeling suspicious behavior through machine learning and fingerprinting techniques. By supporting association with CloudFront, Application Load Balancer, API Gateway and AppSync customers can protect their applications and resources whether all in on the Cloud, maintaining on premise data centers, or using a hybrid Cloud approach.
We build a highly available low latency distributed system that allows customers to propagate changes worldwide in minutes to respond to active attacks in real-time. Using AWS Firehose, customers can store their full WAF logs for compliance and auditing as well as use them for debugging and additional forensics. We support using AWS Config to track historical changes to the rules and metrics associated with their WAF RuleGroups. Using CloudFormation customers can automate the deployment of their WAF Security Automations on the AWS Cloud.
You will play a lead role on the team and influence how we design, develop, build, deploy and support AWS WAF. To be successful in the role, you must be able to research, innovate and create unique solutions. There is no precedent to follow in this problem space. You will be involved from inception to deployment and beyond. You’ll interact with our customers, gathering requirements, designing, implementing, testing and supporting the product operationally; soup to nuts. You will be expected to use your technical background and have a significant impact on the direction of AWS WAF as well as new services that we develop in the future.
We own the direct customer experience as well as the per request processing of rules for CloudFront, API Gateway, and ALB. Not only do we build an AWS Security service, but we’re a customer of AWS using other AWS services to provide the solutions to our customers that scale and seamlessly integrate with their existing workflows. Engineers on our team get to solve some of the hardest computer science problems including building highly available distributed micro-services, global scaling across both AWS Regions and CloudFront edge locations, and processing millions of requests with single digit millisecond latency.
For employees based in Colorado, the base pay range for this position is $143,700.00 to 194,400 to USD per year; however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on payment and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site. - https://www.amazon.jobs/en/landing_pages/benefitsoverview-us https://www.amazon.jobs/en/landing_pages/pto-overview-us
Successful candidates must have a big data engineering background with hands-on
experience in putting experimental machine learning models into production-standard data pipelines:
- Proven track record of leading data engineering projects with large volume of real-time streaming data
- Ability to design, implement and operate data pipelines from various sources
- Expertise with big data processing systems like Apache Spark streaming
- Experience with technologies like AWS EMR, Athena, Step Functions, and Sagemaker.
- Strong coding practices, including good design documentation, unit testing, peer code reviews, and a preference for agile methods.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.
