The Identity Protection team at Sift builds advanced real-time solutions to safeguard user identities and prevent various types of fraudulent activities. This team plays a crucial role in securing digital identities by analyzing fraud patterns, enhancing detection algorithms, optimizing system performance, and promptly addressing security incidents. Joining the Identity Protection team offers a unique opportunity to work on innovative security technologies that protect users and maintain trust in online platforms.

What are we looking for

As a Senior Software Engineer on the Identity Protection team, you will collaborate closely with product managers, data scientists, and engineers to develop and deliver key Identity Protection features that blend machine learning with distributed systems. Specifically, you will:

Build highly scalable, distributed services capable of processing hundreds of millions of events per day
Partner with product management to define and scope project requirements
Design and implement engineering solutions to solve complex customer challenges at scale
Collaborate across engineering teams to deliver reliable and efficient products
Contribute to evolving and improving engineering practices within the team

What would make you a strong fit

5+ years of experience building distributed backend systems using Java
3+ years of experience with cloud infrastructure (e.g., GCP, AWS, Azure)
Strong software engineering fundamentals, including data structures, algorithms, and distributed systems, with excellent debugging, testing, and problem-solving skills
Solid understanding of relational and NoSQL database modeling and design
Excellent communication and collaboration skills, valuing team success above individual accomplishments
A self-starter attitude with a quick learning curve

Bonus points

Experience with stream processing frameworks such as Apache Flink, Apache Beam, or Dataflow
Familiarity with HBase, BigTable, Kafka, ZooKeeper
Experience with practical challenges in ML systems, including feature extraction and definition, data validation, training, monitoring, and management of features and models

A little about us:

Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Brands including DoorDash, Yelp, and Poshmark rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com and follow us on LinkedIn.