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AppDome is seeking a Software Engineer to join its Identity & Reputation team, working on advanced fraud detection capabilities within the Data & Identity Platform. The role involves designing and developing core components of fraud detection systems from prototyping through production-ready releases, building scalable backend services and distributed systems that process data at scale, and writing high-performance, production-quality code in C and C++ optimized for reliability and performance.
You will collaborate closely with security researchers and data teams to develop cutting-edge solutions protecting hundreds of millions of mobile devices. Key responsibilities include taking ideas from rapid proof-of-concept through to production, tackling complex engineering challenges across the full development lifecycle, working with large-scale datasets to create actionable signals and features, and contributing to systems that secure over 50,000 mobile apps protecting more than 1 billion end users globally.
Required qualifications include a B.Sc. in Computer Science, Software Engineering, or equivalent; at least 2 years of experience developing complex enterprise systems; proficiency in C/C++ programming; experience with Python, Java, Linux, and Git; and strong focus on performance, scalability, and reliability in distributed systems. You should be comfortable working with large datasets, collaborating with data science and research teams, and be a quick learner able to adapt to new tools and frameworks.
Preferred qualifications include background in fraud prevention, cybersecurity, or security analytics; experience with mobile app research or development (Android/iOS); experience with machine learning or data science; experience building high-throughput data processing systems; and understanding of threat landscapes and attack vectors.
AppDome is the leader in AI-native mobile business protection, providing cyber and fraud teams with an agentic platform that builds, monitors, and maintains security defenses in Android and iOS apps with no SDKs, no coding, and no disruption to engineering cycles. The platform delivers over 400 security, anti-fraud, anti-bot, and API protection capabilities powered by deep learning models trained on a decade of mobile defense data.
