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.
What You Will Do- 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.
#LI-PP1
Actual compensation will be determined based on several non-discriminatory factors including skills, experience, qualifications, and geographic location.
In addition to base salary, this role may be eligible for bonus or incentive compensation, equity, and a comprehensive benefits package.
A note on AI in our process:
Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards.
Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.
Skills Required
- 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 diagnosing production issues through logs and metrics
- Ability to turn product requirements into practical designs and deliver them 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
Abnormal Security Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Abnormal Security and has not been reviewed or approved by Abnormal Security.
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Fair & Transparent Compensation — Pay is considered aggressively benchmarked to leading tech markets with annual reviews, and feedback suggests engineering and sales roles are compensated competitively with strong upside potential.
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Healthcare Strength — Health coverage is portrayed as robust, including employer-paid premiums for employees in prior postings, One Medical access, and globally designed healthcare and parental leave.
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Leave & Time Off Breadth — Time off provisions include flexible/unlimited PTO, company holidays, and paid parental leave that the company positions as globally available.
Abnormal Security Insights
What We Do
The Abnormal Security platform protects enterprises from targeted email attacks. Abnormal Behavior Technology (ABX) models the identity of both employees and external senders, profiles relationships and analyzes email content to stop attacks that lead to account takeover, financial damage and organizational mistrust. Though one-click, API-based Office 365 and G Suite integration, Abnormal sets up in minutes and does not disrupt email flow. Abnormal Security was founded in 2018 by CEO Evan Reiser, CTO Sanjay Jeyakumar, Head of Machine Learning Jeshua Bratman, and Founding Engineers Abhijit Bagri and Dmitry Chechik. The team previously built behavioral profiling and machine learning technologies at Twitter, Google and Pinterest that are being applied to solve a problem that costs organizations $1 billion per year, according to the FBI. The Abnormal Security platform stops targeted phishing, business email compromise and account takeover attacks that have never been seen before.
