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 are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Email Security. 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 25% of the Fortune 500 (and ever growing).

As a Software Engineer II on our team, you will tackle the exciting challenge of building LLM-based detection systems that significantly enhance our inbound email security product. Your work will involve leveraging the flexibility of LLMs to capture signals from a diverse range of messages, while mitigating the risks associated with deploying LLMs in a customer-facing environment. You will collaborate closely with ML Engineers, Data Scientists, and fellow Software Engineers to minimize the risk and impact of efficacy degradation due to uncontrollable factors. Your efforts will ensure that our inbound email security product remains world-class against an ever evolving threat landscape. Your contributions will directly influence the success of our Email Security product and Abnormal as a whole.

• Design and build our multi-agent architecture to incorporate LLMs into our threat detection engine
• Stay on top of the latest developments in LLMs, and rapidly test those new models/techniques to improve our systems
• Write code with testability, readability, edge cases, and errors in mind biasing towards simple iterative solutions
• Write and review technical design documents
• Participate in Sprint planning, code reviews, standups, and other aspects of the software development life cycle

• 2+ years experience designing and building  software applications
• Experience with large scale systems with an emphasis on data intensive applications that require high availability, throughput, and low latency
• High velocity and creativity in testing out new approaches to solving technical challenges 
• Experience debugging using log analytic tools, metrics, and other signals
• Proven experience translating business requirements into software requirements and delivering high quality implementations
• Strong ability to independently solve complex problems
• Ability to work effectively with cross-functional teams
• BS degree in Computer Science, Software Engineering, Information Systems or other related engineering field

• Experience with Go and Python
• Experience working with LLMs to solve customer facing business problems, where consistency and reliability of the service are essential
• Experience in the cybersecurity industry, financial fraud, application security, or related industries
• Experience with big data, statistics, and Machine Learning

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