Senior Software Engineer

Summary

Join Abnormal Security as a Senior Backend Software Engineer on the Detection Team, where you'll play a crucial role in scaling and optimizing the high-throughput, low-latency scoring infrastructure for their cutting-edge email and cloud-based attack detection technology. You'll be responsible for architecting scalable solutions, collaborating with ML Engineering teams, and mentoring junior engineers. This role requires extensive experience with real-time, online, high-throughput, and low-latency distributed systems, a proven track record of maintaining high uptime for services handling significant QPS, and strong leadership skills in driving complex projects to completion.

Requirements

• 5+ years of professional experience as a hands-on engineer building and scaling data-intensive products
• Extensive experience with real-time, online, high-throughput & low-latency distributed systems
• Proven ability to maintain 99.99% uptime for services handling 20k+ QPS
• Strong track record of cross-functional collaboration and driving complex projects to completion
• Demonstrated leadership in setting and maintaining high standards for project execution and code quality
• Experience in fast-paced or start-up like environment
• Experience with cloud-native architectures and microservices
• Experience with event-driven architecture such as Kafka, Pub/Sub, etc

Responsibilities

• Lead the architecture, design, and implementation of highly scalable backend services and infrastructure supporting our world-class Detection Engine
• Spearhead critical projects to meet ambitious goals, such as scaling components of Detection's Scoring Pipeline by 10x while maintaining or improving performance
• Collaborate closely with ML Engineering teams to gather requirements, provide technical leadership, and drive execution of infrastructure improvements
• Mentor and coach junior engineers through 1-on-1s, pair programming, and high-quality code and design reviews
• Continuously optimize system performance, reliability, and efficiency to meet growing demand and evolving threat landscape

Preferred Qualifications

• Familiarity with ML systems/products and distributed system technologies (e.g., Python, Golang, Kafka, Redis, Docker, Kubernetes, feature serving platforms, ML training and serving infrastructures)
• Hands-on experience optimizing high-throughput online systems
• Familiarity with the cybersecurity industry or fraud detection and its unique challenges