At Abnormal AI, we’re building the infrastructure that powers our AI-native cybersecurity platform, which protects the world’s largest enterprises from sophisticated attacks. The Platform & Infrastructure (PI) division provides the core systems that enable all Abnormal products to operate reliably, at scale, and with high performance.
You’ll join a team that owns critical services in cloud infrastructure, data platforms, observability, and development tooling.
What We’re Looking For:● Ownership & Impact: You’re growth-oriented, take ownership of your work, and are eager to make a significant impact.
● Continuous Learner: Looking to grow as an engineer as part of a strong team, learning from established engineers, product managers, and designers.
● Strong Communicator: You excel in communication, with the ability to workautonomously and asynchronously with different teams.
Must Have Skills● 2+ years of experience as a software engineer with a strong foundation in coding and problem-solving.
● Hands-on experience in backend development using Python, with exposure to cloud-native environments.
● Solid understanding of databases, REST APIs, and data pipelines.
● Familiarity with LLM's and AI development tools such as Cursor, GitHub Copilot, or Claude
● Demonstrated passion for building scalable, enterprise-grade systems that operate reliably in production.
● Curiosity and eagerness to learn about distributed systems, orchestration, and cloud infrastructure.
Nice to Have● Familiarity with containerization (Docker, Kubernetes).
● Exposure to observability tools (Prometheus, Grafana).
● Interest in data platforms, streaming systems, or infrastructure-as-code.
What You’ll Do
As part of our Platform & Infrastructure team, you will:
● Leverage AI-powered Development – Use Cursor, Copilot, and other AI tools to
accelerate development, automate workflows, and improve reliability.
● Build Foundational Systems – Design and maintain core backend services, infrastructure tooling, and data pipelines that support all Abnormal products.
● Optimize for Scale – Improve performance and resilience of systems handling billions of events daily.
● Collaborate Across Teams – Partner with Detection, Data Platform, and Product Engineering teams to ensure seamless integration and platform consistency.
● Drive Reliability and Observability – Build automated monitoring, alerting, and logging to ensure system health and performance at scale.
#LI-FS1
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
- 2+ years of experience as a software engineer
- Strong foundation in coding and problem-solving
- Hands-on backend development experience using Python
- Experience with cloud-native environments
- Understanding of databases, REST APIs, and data pipelines
- Familiarity with LLMs and AI development tools such as Cursor, GitHub Copilot, or Claude
- Experience building scalable, enterprise-grade systems that operate reliably in production
- Interest in distributed systems, orchestration, and cloud infrastructure
- Familiarity with Docker and Kubernetes
- Exposure to Prometheus and Grafana
- Interest in data platforms, streaming systems, or infrastructure as code
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.
