About the Role

Abnormal AI is seeking an experienced Engineering Manager to lead our Aggregates Systems team, which owns some of the most mission-critical infrastructure in the company. These systems sit at the core of our detection architecture, transforming raw behavioral signals into high-quality aggregate datasets that directly power security decisions across all Abnormal products.

The Aggregates Systems operate at extreme scale—processing tens of billions of events per day and approaching one million events per second at peak—and correctness, availability, and timeliness are non-negotiable. In this role, you will manage and grow a team of engineers responsible for building, operating, and evolving large-scale batch and real-time aggregation systems that Abnormal’s detection, messaging, and customer trust depend on. You will partner closely with engineering, data science, product, and infrastructure teams to ensure these systems remain reliable, performant, and scalable as the company grows.

What You’ll Do

Technical & Systems Leadership

• Own the technical direction, reliability, and long-term evolution of aggregation systems spanning both batch and real-time processing.
• Guide architectural decisions for distributed data processing, storage, and retrieval systems with strict correctness, latency, and availability requirements.
• Ensure aggregation systems consistently meet SLAs for data freshness, accuracy, and uptime across detection and messaging use cases.
• Act as a senior technical steward for systems whose failure or inaccuracy would have direct customer and security impact.
  
  

People Management & Team Development

• Manage, mentor, and develop a team of software engineers working across batch and streaming aggregation systems.
• Foster a culture of technical excellence, operational ownership, and continuous improvement.
• Support career growth through coaching, feedback, and clear performance expectations.
  
  

Cross-Functional Collaboration

• Partner with Detection Engineering, Data Science, Product, and Infrastructure teams to translate detection requirements into scalable aggregation capabilities.
• Collaborate with stakeholders to define roadmaps that balance feature delivery with system stability and long-term maintainability.
• Serve as a technical and organizational point of accountability for aggregation systems.
  
  

Operational Excellence

• Drive strong operational practices, including monitoring, alerting, incident response, and post-incident analysis.
• Improve observability, data quality validation, and resiliency across batch and real-time systems.
• Ensure systems scale efficiently as data volume, customer footprint, and use cases expand.
  
  

Systems You’ll Own

Aggregates System

• In Online systems, the team operates low-latency aggregation systems designed to process high-throughput event data with strict timeliness guarantees.
• Composed of event producers, a Kafka-based event stream, and a signals stack including ingestion and storage update services.
• Enable fast, flexible retrieval of aggregate values for security and messaging applications.

• In Offline systems, the team operates batch processing systems that transform large volumes of raw behavioral signals (e.g., emails and user activity) into comprehensive aggregate datasets.
• Operate on scheduled cadences and support long lookback windows for historical analysis and trend detection.
• Play a foundational role in determining whether messages are safe or malicious by powering detection logic and models.

What We’re Looking For

Required Qualifications

• 5+ years of software engineering experience, with 2+ years in an engineering management role.
• Strong experience designing and operating distributed, data-intensive systems.
• Hands-on familiarity with batch processing and/or real-time streaming systems (e.g., Kafka, Spark, Flink, Beam).
• Proven ability to lead complex, high-impact technical initiatives and make sound architectural tradeoffs.
• Excellent communication skills and experience working cross-functionally.
  
  

Preferred Qualifications

• Experience building or owning mission-critical aggregation or signals systems.
• Familiarity with data correctness, quality guarantees, and observability in production environments.
• Experience in security, messaging, or other high-reliability SaaS domains.
• Track record of scaling systems and teams in fast-growing organizations.
  
  

#LI-ML1

About the Role

What you will do

Must Haves

Nice to Haves

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The Opportunity

Abnormal AI is revolutionizing cybersecurity by leveraging AI-native technologies to combat modern cyber threats. We’re building a team of top-tier engineers who are excited to use Generative AI tools like Cursor, GitHub Copilot, and Claude to redefine how software is built – faster, smarter, and more efficient.

We are seeking a highly skilled Software Engineer II to help shape the future of AI-powered application development. If you’re passionate about cutting-edge technology, scalable systems, and solving real-world challenges, this is your opportunity.

About You

You are someone who wants to make an impact. You are passionate about solving customer problems and have built up a base of skills in backend and distributed systems development to do so. You want to apply those skills on a problem that leaves the world in a better place. 

We are a scrappy team: we are building a new product from scratch – this means you should be comfortable with a level of uncertainty beyond what you’d find at a more mature company or even a more mature team at Abnormal. Not every project will come with a well defined PRD - that’s expected and we expect this engineer to go dig in and figure out what to do. This also means occasionally we’ll ask you to do things that may not strictly fit the role of a “backend engineer” - it might mean jumping on a customer call, or digging in to help fix a frontend bug. 

We are also not only a remote team, but a very distributed team, as such you will need to have excellent communication skills across both verbal and written mediums. You will need to be just as comfortable on a zoom call as writing a 1 pager project proposal to be shared across the team for technical feedback. 

In this job, you will bring these skills:

• Experience with building and operating distributed systems and services at a high scale (~billions of transactions each day)
• Streaming data systems - using Kafka, Spark, Map/Reduce or similar to process large data sets
• Working on large scale data storage systems, such as DynamoDB, Aerospike, Redis and Databricks
• 3-5 years of overall software engineering experience
• Strong sense of best practices in developing software

Role Responsibilities

• Build out storage and retrieval infrastructure for our Aggregates Platform
• Allows our various ingestion pipelines and detection algorithms to send us billions of data points per day to be stored and processed.
• Making sure that such a large scale data architecture works at our scale, low latency requirements and scales with our cellular architecture
• Work on a series of projects towards scalability, reliability and cost optimisations.
• Partner with our various customer teams
• Understand the use cases and scale requirements of our customers and work to implement them. 
• Help build our group through excellent interview practices
• This engineer must be able to accurately assess candidates technical skills, cultural fit and likelihood of success at Abnormal to ensure we hire the right team. 
• Be a talent magnet - someone who through the interview process demonstrates their own strengths in a way that attracts candidates to Abnormal and to the Aggregates team and ensures that we close the candidates we want to close. 

#LI-RT1

At Abnormal AI, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. 

Abnormal is recognized as a top cybersecurity startup (Leader in the 2025 Gartner Magic Quadrant for Email Security Platforms), securing a Series D funding of $250 million at a $5.1 billion valuation in August 2024. 

About The Team 

The team is responsible for the ownership, development, and operation of the infrastructure and ML models, customer facing APIs and internal tools that drive Abnormal's Account Takeover (ATO) protection product. This product is crucial for detecting malicious activity and safeguarding customers from account theft.

About The Role

We are looking for a Senior Software Engineer to take ownership of complex feature delivery and technical design for our ATO platform. This pivotal role involves evolving the platform to scale with expanding product requirements. The position requires a blend of hands-on backend systems development, production ownership, stakeholder management, and team mentorship. The core goal is to enhance system reliability, reduce latency, and significantly accelerate feature release cycles.

What You’ll Do

Technical Delivery & Excellence

• Design, build, and iterate on scalable backend and ML systems, APIs, frameworks, and internal tools 
• Own end-to-end delivery of complex features that directly impact customer experience.
• Ensure stability, reliability, and operational excellence of critical systems.
• Write clean, testable, and resilient code with attention to edge cases and performance.
• Write and review technical design documents and influence adoption across the team.
• Participate in code and design reviews, and contribute to on-call rotations.

Leadership & Collaboration

• Collaborate with product managers, designers, and engineers to align on specifications and priorities.
• Break down complex projects into clear executable steps and drive them to completion.
• Actively contribute to roadmap discussions and propose long-term technical plans.
• Communicate effectively in an async-first environment, providing clarity on updates, challenges, and solutions.
• Mentor peers, share knowledge, and influence engineering practices across the team.

What We’re Looking For

• Ownership & Growth: A senior engineer mindset—able to independently lead complex projects and grow into a technical leader within the team.
• Attention to Detail: Deep focus on code quality, reliability, monitoring, and performance.
• System Thinker: Ability to anticipate long-term scaling needs and design resilient architectures.
• Strong Collaborator: Comfortable influencing cross-team goals, mentoring peers, and working in a distributed environment.
• GenAI Affinity: Proactive in leveraging modern developer productivity tools, including GenAI assistants, to accelerate delivery.

Must-Have Skills

• 7+ years of industry experience, with proven expertise as a Senior Software Engineer.
• Strong backend proficiency in Python, with experience designing and scaling production systems.
• Proven experience with large scale system design, building resilient, scalable, and fault-tolerant applications.
• Strong knowledge of relational databases and modern data storage technologies .
• Familiarity with service-to-service communication (gRPC, Kafka) and caching (Redis).
• Experience with AWS cloud services (S3, RDS) and deployment practices.
  Familiarity with containerization and orchestration (Docker, Kubernetes, Helm).
• Strong understanding of service health, monitoring, and incident response practices.
• Experience writing technical design documents and influencing adoption across teams.

#LI-RT1

About the Role

The Inbound Data Team (IDT) owns the integrations and data ingestion systems that make critical signals available that powers multiple downstream products and related detection/remediation services. SaaS integrations extend coverage beyond email to provide cross-platform visibility into user behavior and centralize compromised account detection and remediation across identity, collaboration, and cloud infrastructure applications. This product line (and the downstream consumers it supports) is one of Abnormal’s biggest strategic bets and will drive significant company growth over the next several years. IDT’s work is foundational: by delivering reliable, timely, and contextual data, the team enables downstream detection systems, ML models, and remediation processes to operate effectively.

We’re hiring a Senior Software Engineer (SWE3) to design, build, and operate high-scale, low-latency ingestion and data-integration systems that serve multiple product lines. This role combines hands-on backend systems work, production ownership, and mentorship responsibilities to increase reliability, reduce latency, and accelerate feature delivery across the organization.

What We’re Looking For:

• System design & communication: Excellent system-design skills and the ability to clearly communicate tradeoffs across product, ML, security, and platform teams.
• Proven production scale experience: Experience designing and operating services at very large scale (e.g., 1B+ transactions/day or equivalent high throughput).
• Backend systems expertise: Hands-on experience building production-grade backend systems (Go/Python) and services that run reliably in production.
• Distributed systems expertise: Proven track record designing and operating large-scale, low-latency distributed systems under real production load.
• Ownership & impact: A proactive engineer who takes full ownership of complex projects and drives them to measurable results.
• Detail-Oriented: You’re meticulous about code quality, testing, performance and observability, ensuring that every aspect of your work meets the highest standards.
• Growth Mindset: You’re committed to continuous learning and personal growth, leveraging opportunities to expand your skills alongside seasoned professionals in engineering, product, and design.
• Technical Proficiency: You’re comfortable with test-driven development and thrive in complex organizations where standardized interfaces and best practices are key to success.

What You’ll Do

1. Design and Development: Lead the design and development of robust, scalable, and secure backend systems using Golang, Python. You will own the delivery of end-to-end projects, from conceptual design through to deployment, ensuring that each project meets the high standards expected within the Division.
2. Ownership & Technical Leadership: Take full ownership of key deliverables within the Division’s Quarterly Roadmap and define milestones, and drive projects to successful completion.
3. Reliability & Observability: Ensure system SLOs/SLAs for latency, availability, throughput, and correctness; instrument services with tracing, metrics, dashboards, and alerts so downstream teams can rely on the data.
4. Support and On-call: Provide expert technical support, troubleshoot complex issues, and participate in on-call rotations to maintain system reliability and performance.
5. Cross-Division Leadership: Align teams around key projects, de-risk complex initiatives, and ensure seamless execution across the Division. As a Senior Engineer, you’ll be a multiplier, enhancing the capabilities of those around you.
6. Collaboration and Communication: Engage in asynchronous communication with team members to share updates, resolve challenges, and propose solutions. You’ll also participate in code reviews and system design discussions, contributing to the team’s technical excellence.
7. Continuous Learning and Improvement: Actively share your knowledge with the team and participate in professional development activities to keep your skills sharp and relevant.

Must Have Skills

• 6+ years of industry experience as a Backend Software Engineer, with demonstrated impact building and operating production-grade Go and/or Python services at scale (e.g., services processing 1B+ transactions/day or equivalent). 
• Strong understanding of Golang and its ecosystem, as well as Python and REST frameworks.
• Practical experience with streaming/messaging systems (Kafka / Kinesis / Pulsar) and stream processing frameworks or equivalents.
• Familiarity with AWS services and deployment practices.
• Proficiency in containerization using Docker or similar technologies.
• Solid understanding of database systems and SQL proficiency.
• Excellent system design and communication skills for cross-team collaboration.

#LI-AB2

Abnormal AI is looking for a Machine Learning Engineer to join the Account Takeover Detection team. At Abnormal, we protect our customers against nefarious adversaries who are constantly evolving their techniques and tactics to outwit and undermine the traditional approaches to Security. Abnormal is recognized as a top cybersecurity startup (Leader in the 2024 Gartner Magic Quadrant for Email Security Platforms), securing a Series D funding of $250 million at a $5.1 billion valuation in August 2024. Our 100% YoY growth in annual recurring revenue highlights the trust our behavioral AI system has earned in protecting over 20+% of the Fortune 500. We continue to grow and innovate to stay ahead of the evolving threat landscape.

The Team 

In a landscape where a single successful attack can lead to financial losses of millions of dollars, the Account Takeover team (ATO) is at the forefront of customer protection, playing a central role in building systems that can detect malicious activity and protect customers from account takeovers. The Account Takeover Detection team’s mission is to leverage cutting-edge machine learning technologies for proactive detection and prevention of account takeover attempts, continuously improving ATO capabilities to stay ahead of evolving fraud patterns and safeguard user accounts with unparalleled accuracy and efficiency

The Role

This role offers the opportunity to contribute significantly to our team's charter, direction, and roadmap by defining technical goals, addressing customer problems, maintaining production models, and ensuring operational excellence. The ideal candidate will have a background in machine learning, data science, and software engineering, with the ability to design, develop, and implement robust machine learning models and systems in production. 

Key Responsibilities

• Contribute to the development of machine learning algorithms and models for behavioral modeling and cybersecurity attack detection.
• Work with cross-functional teams to understand requirements and translate them into effective machine learning solutions.
• Conduct exploratory data analysis, feature engineering, model development and evaluation.
• Work with infrastructure & product engineers to productionize models and new ML-based features
• Monitor and improve production models through feature engineering, rules, and ML modeling as part of a team effort.
• Participate in code reviews to ensure the quality and maintainability of ML systems.
• Stay updated on the latest research in the field of machine learning, data science, and AI.
• Adopt and contribute to the development of machine learning best practices within the organization.

Required Skills:

• Proven experience as a Machine Learning Engineer or similar role in a commercial environment (3+ years).
• Knowledge of machine learning algorithms, statistics, and predictive modeling.
• Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally. pytorch/tensorflow.
• Awareness of machine learning operations (MLOps) and productionization of ML models best practise.. 
• Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business questions and assess system efficacy.
• Ability to communicate technical ideas in a clear, non-technical manner.

Optional Skills:

• Familiarity with LLMs
• Previous experience in Cybersecurity
• Previous experience with Airflow or similar ML pipeline orchestration tools 
• Experience with large scale ML system and data infrastructure
• Previous experience in behavioural modeling techniques
• PhD or equivalent proven experience in ML research
• Familiarity with cloud computing platforms (AWS, Azure

#LI-RT1