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Abnormal Security

Staff Software Engineer - Detection Serving & Signals

Job Posted 4 Days Ago Reposted 4 Days Ago
Remote
Hiring Remotely in USA
210K-247K Annually
Senior level
Remote
Hiring Remotely in USA
210K-247K Annually
Senior level
The Staff Software Engineer will lead the design and implementation of scalable backend services, optimize performance, and mentor junior engineers in a fast-paced environment.
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About the Role

Abnormal Security is seeking a Staff Backend Software Engineer to join our Detection Team. The Detection Division is at the forefront of developing cutting-edge technology to identify and thwart sophisticated email and cloud-based attacks that were previously undetectable, contributing to a safer digital world. As a Staff Software Backend Engineer focusing on the Detection's Serving Platform, you will be instrumental in scaling and optimizing our high-throughput, low-latency scoring infrastructure to ensure a fast, responsive, stable, and reliable experience for our customers .

The ideal candidate will possess:

  • A proven track record of scaling high-throughput, low-latency model scoring infrastructure
  • Experience in maintaining 99.99% uptime for services handling 50k+ QPS
  • A first-principles approach to architecting scalable, customer-centric solutions
  • A passion for solving complex, real-world problems with pragmatic solutions
  • Strong ownership mentality and impact-driven outlook on efforts and growth
  • Ability to iterate rapidly and autonomously on novel challenges
  • Experience with performance engineering - in identifying and resolving bottlenecks in systems and improving the performance in an iterative way

Key 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

Requirements

  • 8+ 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 50k+ 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.

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
  • MS or PhD in Computer Science, Electrical Engineering, or a related field
  • Familiarity with the cybersecurity industry or fraud detection and its unique challenges

#LI-ML1

At Abnormal Security certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. We know that benefits are also an important piece of your total compensation package. Learn more about our Compensation and Equity Philosophy on our Benefits & Perks page.

Base salary range:

$209,800$246,800 USD

Top Skills

Docker
Go
Kafka
Kubernetes
Python
Redis

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