Sift

Staff Cloud Platform Engineer- Core Infra

United States

Sift Logo
$164,200 – $222,200Compensation
Senior (5 to 8 years)Experience Level
Full TimeJob Type
UnknownVisa
Enterprise Software, Data & AnalyticsIndustries

Requirements

Candidates must have 8+ years of experience as a Software Engineer focused on infrastructure/platform services or in a Site Reliability Engineering (SRE) role. Strong programming skills in languages such as Java, Scala, or Python are required, along with experience designing and implementing distributed systems. Candidates should have experience building and managing cloud infrastructure on AWS or GCP and expertise in building infrastructure as code using tools like CloudFormation or Terraform. Proficiency in setting up and managing monitoring and alerting systems is essential, as well as familiarity with Docker and Kubernetes. Strong experience in troubleshooting production system issues and a solid understanding of configuration management tools are also necessary.

Responsibilities

The Staff Cloud Platform Engineer will own the availability, performance, and scalability of Sift’s primary online storage systems and infrastructure. They will design and build immutable infrastructure and fault-tolerant systems, implement multi-region deployments, and solve complex problems related to data volume and request rates. The engineer will optimize local development workflows, design services for data store interaction, and develop tools for monitoring and repairing distributed systems. Additionally, they will provide design support to internal teams and participate in on-call support and incident response activities.

Skills

Java
Scala
Python
AWS
GCP
CloudFormation
Terraform
Monitoring
Alerting
Distributed Systems
Infrastructure as Code

Sift

Real-time fraud detection and prevention platform

About Sift

Sift provides a platform focused on detecting and preventing online fraud in real-time, catering to clients in e-commerce, fintech, and digital marketplaces. The platform uses machine learning and artificial intelligence to analyze large datasets, allowing it to identify fraudulent activities effectively. One of its standout features is dynamic friction, which ensures that genuine users have a smooth experience while preventing fraudsters from accessing services. Sift's business model is subscription-based, with fees that depend on transaction volume and service level. Additionally, Sift offers services like chargeback management and dispute resolution, which add further value to its offerings. The company's goal is to enhance digital trust and safety for businesses by providing tools that help them make informed decisions and protect against fraud.

Key Metrics

Bristol, United KingdomHeadquarters
2011Year Founded
$4.4MTotal Funding
SERIES_ACompany Stage
AI & Machine Learning, Financial ServicesIndustries
51-200Employees

Risks

Rise of app-enabled friendly fraud challenges Sift's mobile fraud detection capabilities.
Reliance on third-party delivery apps by QSRs introduces new fraud risks for Sift.
Complex payment processes may complicate Sift's integration and effectiveness in fraud prevention.

Differentiation

Sift offers a comprehensive platform for real-time online fraud detection and prevention.
The company uses machine learning and AI to analyze vast amounts of data effectively.
Sift's dynamic friction feature ensures seamless user experience while blocking fraudsters.

Upsides

Growing demand for AI-driven fraud detection in QSRs presents expansion opportunities for Sift.
Digital-first banks' need for effective authentication aligns with Sift's fraud prevention solutions.
Global trend towards secure payment systems supports Sift's mission for digital trust and safety.

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