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 demonstrated leadership 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
Benefits
- Bonus
- Restricted stock units (RSUs)
- Health insurance
- Retirement benefits
- Life and disability insurance
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