The Fraud Detection team is looking for a strong Senior Backend Engineer to help scale and evolve our industry-leading real-time fraud prevention systems.
We develop high-throughput, low-latency services that power real-time decision-making at scale. Our platform combines modern backend engineering with advanced streaming, big data technologies, and AI-powered models to protect businesses and their users from fraud—instantly and effectively.
This role is critical in delivering scalable backend infrastructure to power our machine learning-driven fraud detection capabilities.
What You’ll Do
- Design and Build Scalable Backend Services:
- Design and implement real-time streaming applications for processing high-throughput data using Kafka and gRPC
- Develop scalable and reliable streaming solutions for fraud detection and prevention.
- Develop and Optimize ETLs:
- Build, and maintain batch pipelines for data enrichment, normalization, and aggregation using tools like Spark and BigQuery.
- Ensure data pipelines are robust, scalable, and cost-efficient.
- Support Data Science and ML-Ops:
- Collaborate with Data Science teams to operationalize machine learning models in real-time streaming environments and batch ETLs.
- Focus on Performance and Resilience:
- Continuously improve the throughput, latency, and fault tolerance of critical services operating under high load and real-time constraints.
- Collaborate Across Teams:
- Work closely with Fraud Data Scientists, and Product Managers to deliver impactful solutions.
- Partner with stakeholders to understand the business impact of fraud detection and align technical solutions with business needs.
- Innovate and Improve:
- Continuously improve the scalability and performance of existing systems.
- Explore and integrate new tools and technologies to enhance streaming and batch-processing capabilities.
- Backend Engineering Expertise:
- 5+ years of experience designing and building scalable, resilient backend systems with a strong focus on performance, reliability, and clean architecture.
- Distributed Systems & Scalability:
- Hands-on experience with high-throughput, low-latency, and mission-critical distributed systems operating at scale.
- Strong Big Data Foundations:
- Deep understanding of data pipelines and distributed processing frameworks such as Spark and BigQuery, with a focus on performance, efficiency, and cost optimization.
- Data Science and ML Collaboration:
- Exposure to machine learning workflows, including data preparation, model deployment, and monitoring.
- Collaboration & Ownership:
- A strong sense of ownership, paired with excellent collaboration skills, to work effectively across engineering, product, and data teams.
- Knowledge in Big Data - Scala, Spark, Data pipeline for example.
- Recommended by an AppsFlyer employee
“As a Customer Obsessed company, we must first be Employee Obsessed. We need to make sure that we provide the team with the tools and resources they need to go All-In.” Oren Kaniel, CEO
במקום לחפש לבד בין מאות מודעות – תנו ל-Jobify לנתח את קורות החיים שלכם ולהציג רק הזדמנויות שבאמת שוות את הזמן שלכם.
חינם, מהיר, מותאם אישית.
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