Design, build, and operate real-time abuse and fraud detection services processing high-volume event streams
Author and evolve detection rules and signals using streaming frameworks
Develop and maintain cloud-native services and APIs in Python and Java
Build and operate event-driven pipelines using AWS services such as Kinesis, Lambda, S3, and DynamoDB
Collaborate closely with security, compliance, and product partners to turn new threat patterns into production mitigations
Ensure systems are observable, scalable, and resilient in a production AWS environment.

Requirements

Strong experience building production-grade systems in Python (Java experience a plus)
Hands-on experience with AWS, especially Kinesis, Lambda, S3, DynamoDB, and IAM
Experience with Apache Flink, Kinesis Streams, or similar streaming rule engines
Background in data engineering, data analytics, or applied data science
Exposure to machine learning or statistical techniques used in detection, scoring, or classification
Ability to design and maintain RESTful APIs and backend services
Comfortable working in Linux-based production environments
Strong problem ownership, bias for action, and ability to operate independently in a small team.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

PythonJavaAWSKinesisLambdaS3DynamoDBApache FlinkRESTful APIsdata engineering

problem ownershipbias for actionindependencecollaboration