Software Engineer II, Attack Detection

At Abnormal AI, we are on a thrilling mission to safeguard the world's largest enterprises against a vast range of relentless email attacks. We protect our customers against adversaries who constantly evolve their techniques and tactics to outwit and undermine traditional email security approaches. That's what makes our novel behavioral- based approach so...Abnormal. Abnormal has constantly been named as one of the top cybersecurity startups and our behavioral AI system has helped us win various cybersecurity accolades resulting in being trusted to protect more than 15% of the Fortune 500 (and ever growing).

As a Software Engineer II, you will build customer-facing security features and the software that supports them. Projects may include detection services or AI agents that use models and software tools to investigate suspicious activity. Other projects support model development and evaluation, mostly driven by automated agentic loops.

You will collaborate closely with ML Engineers, Data Scientists, and fellow Software Engineers to turn new approaches into reliable production systems and in turn help us catch more attacks and improve security investigations while limiting false positives and cost. Your work will help keep our inbound email security product world-class in an ever-evolving threat landscape. Your contributions will directly influence the success of our Email Security product and Abnormal as a whole.

Strong software engineering skills are essential. Practical machine learning experience is preferred.

• Build backend services and data pipelines for customer-facing security features.
• Integrate machine learning models and large language models into detection and investigation workflows.
• Develop AI agents that analyze suspicious activity and support security investigations.
• Build tools that make model training repeatable, agent-driven, and help engineers evaluate AI systems.
• Evaluate changes against real attack patterns and investigate missed attacks and false positives.
• Improve system reliability and performance within latency and cost limits.
• Write tested, readable code and contribute to technical designs and code reviews.
• Own well-defined features from design through release and monitor their behavior in production.

• A bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related engineering field.
• At least 2 years of experience in software design and development.
• Experience with backend services or data-intensive applications where reliability and performance matter.
• Strong programming skills in a general-purpose language and knowledge of data structures and software design.
• Experience with automated tests and diagnosis of production issues through logs and metrics.
• Ability to turn a product requirement into a practical design and deliver it with guidance on larger technical decisions.
• Clear technical communication and effective collaboration with other engineers.

• Hands-on machine learning experience from industry, research, or substantial projects.
• Experience with large language models or AI agents, including evaluation of accuracy and reliability.
• Experience with statistical evaluation of classifiers, including precision and recall.
• Experience with Python or Go.
• Experience with data pipelines or tools that make model experiments reproducible.
• Experience with cybersecurity or fraud detection.

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