About The Position

Abnormal AI is looking for a Software Engineer II to join the Detection Team. The Detection Division is focused on building the world’s most advanced technology to identify and stop email and cloud-based attacks that were previously undetectable, helping make the world a safer place. As a Software Engineer focused on building systems for Detection’s Model Platform, you will be responsible for making feature development at Abnormal a fast, responsive, stable, and confident experience for our ML and Data Science teams. The ideal candidate brings a first-principles approach to building scalable, customer-centric solutions, an ownership-oriented mindset, and the ability to iterate quickly and autonomously on novel problems.

Requirements

  • 4+ years of experience as a Software Engineer or in a similar role, with hands-on experience building data-focused solutions.
  • Proficiency leveraging AI tools to accelerate engineering outcomes through discovery, design, implementation, and rollout of software systems.
  • Experience maintaining large-scale distributed systems on cloud platforms such as AWS, GCP, or Azure, including a strong grasp of best practices in cloud-based engineering.
  • Experience with real-time and near real-time data pipelines or streaming services.
  • Strong fundamentals in computer science, data structures, and performance optimization.
  • BS degree in Computer Science, Applied Sciences, Information Systems, or other related engineering field.

Nice To Haves

  • Familiarity with our stack: AWS, Kubernetes, Python/Django, Golang, and Postgres.
  • Experience building scalable, enterprise-grade applications.
  • Experience with web security (e.g., OWASP Top 10).
  • Familiarity with AI development tools such as Cursor, GitHub Copilot, or Claude.

Responsibilities

  • Leverage industry-standard AI tools to architect, design, build, deploy, and maintain Model Serving infrastructure that supports a world-class Detection Engine.
  • Own projects that scale our model serving and data processing services to handle 10x the traffic we serve today.
  • Own real-time and near real-time streaming pipelines, and online feature serving services.
  • Collaborate closely with MLE and Data Science teams by distilling feedback, correlating it to strategy, and executing.
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