About the Role
At Abnormal Security, we are on a mission to safeguard the world's largest enterprises against relentless email and collaboration security attacks. We seek an Engineering Manager to lead the Detection Internal Tools team. This team is responsible for building the platforms and tools that empower our detection engineers to improve the accuracy and efficiency of our detection systems. The team also drives misclassification analysis, data quality for machine learning (ML) models, and customer interaction around detection concerns.
As the Engineering Manager, you will lead a team focused on delivering tools and systems that ensure all detection misclassifications are easily assessed, analyzed, and improved. You will drive the development of detection tools, ML data quality analysis, and support the smooth flow of customer detection feedback. You will play a key role in managing team performance, setting strategic goals, and mentoring engineers to excel in a fast-paced cybersecurity environment.
Core Responsibilities:
- Own the design, development, and operation of tools for analyzing detection systems misclassifications and improving ML data quality.
- Collaborate with Product Managers, Data Scientists, and ML Engineers to prioritize detection improvements and system stability.
- Scale systems for high throughput, ensuring real-time, low-latency responses while maintaining data accuracy and quality.
- Lead the development of internal tools for managing detection workflow and supporting cross-functional engineering teams.
- Ensure effective customer feedback pipelines are built to automatically process and respond to detection issues.
- Mentor, develop, and grow the engineers on your team, ensuring they have a clear career progression and high levels of engagement.
- Ensure project execution aligns with the company’s detection strategy and maintain continuous stakeholder communication.
What you will do
- Enhance the speed and quality of detection systems development.
- Power pipelines to process and respond to customer feedback responsibly.
- Automate processes to improve customer responses.
- Develop, design, modify, and test systems for enhanced data quality and understanding.
- Collaborate with Technical Program Managers, Product Managers, Data Engineers, Data Scientists, and operational and engineering teams to implement, verify, and iterate on product development.
- Exercise sound judgment in selecting methods and techniques for problem-solving.
- Drive development best practices with testability, readability, edge cases, and errors in mind.
Must Haves
- Familiarity with large-scale solutions or environments that involve complex integrations, demanding latency requirements, or significant throughput challenges.
- Proven ability to translate business requirements into detailed software requirements, effectively articulating systems design to technical and non-technical stakeholders alike.
- Proven experience working effectively with cross-functional teams, demonstrating the ability to collaborate with a diverse range of stakeholders.
- Ability to lead and motivate team members, setting high standards and expectations for project execution, both for themselves and their collaborators.
- A Bachelor of Science degree in Computer Science, Applied Sciences, Information Systems, or a closely related engineering field.
- Professional Experience:
- At least 5 years of professional, production-level experience in full-stack development, showcasing a comprehensive understanding of both front-end and back-end technologies.
- 5 years of management experience
Nice to Have
- Experience in building teams from the ground up
- MS degree in Computer Science, Electrical Engineering or other related engineering field
- Experience with algorithms and optimization
- Familiarity with cyber security industry
Top Skills
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.