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Engineering Manager - Aggregates Systems

Оценка ИИ

Отличная вакансия в быстрорастущем AI-единороге с прозрачным диапазоном зарплаты, удаленным форматом работы и возможностью работать над сложнейшими инженерными задачами мирового уровня.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена необходимостью совмещать глубокие технические знания в области Big Data (Kafka, Spark, Flink) с навыками управления командой в условиях экстремальных нагрузок (1 млн событий в секунду).

Анализ зарплаты

Медиана225 000 $
Рынок180 000 $ – 280 000 $
Оценка ИИ

Предлагаемая зарплата ($187k - $270k) полностью соответствует и даже немного превышает рыночные стандарты для Engineering Manager в США, особенно учитывая удаленный формат работы.

Сопроводительное письмо

I am writing to express my strong interest in the Engineering Manager position for the Aggregates Systems team at Abnormal AI. With over five years of experience in software engineering and a proven track record of managing high-performance teams, I am particularly drawn to this role because of the extreme scale and mission-critical nature of your detection architecture. My background in building distributed data-intensive systems aligns perfectly with your need for a leader who can balance technical excellence with operational reliability.

In my previous roles, I have successfully led initiatives involving real-time streaming with Kafka and large-scale batch processing, similar to the systems powering Abnormal’s behavioral signals. I am passionate about fostering a culture of technical ownership and mentoring engineers to reach their full potential. I am eager to bring my expertise in architectural tradeoffs and cross-functional collaboration to help Abnormal AI continue its impressive growth while maintaining the highest standards of data correctness and system availability.

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Откликнитесь в abnormalsecurity уже сейчас

Присоединяйтесь к Abnormal AI, чтобы возглавить разработку критически важной инфраструктуры данных и защитить тысячи компаний от киберугроз.

Описание вакансии

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

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.

Base salary range:

$187,400—$269,500 USD

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.

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Навыки

  • Kafka
  • Apache Spark
  • Apache Flink
  • Apache Beam
  • Distributed Systems
  • Batch Processing
  • Real-time Streaming
  • SaaS
  • Observability
  • Infrastructure

Возможные вопросы на собеседовании

Проверка опыта работы с высоконагруженными системами, упомянутыми в описании.

Расскажите о самом сложном инциденте в распределенной системе обработки данных, которым вы управляли. Как вы координировали команду и какие выводы сделали?

Оценка способности принимать архитектурные решения, критичные для бизнеса.

Как вы подходите к выбору между пакетной (batch) и потоковой (streaming) обработкой для конкретной бизнес-задачи? Приведите пример компромисса между задержкой и точностью.

Проверка навыков управления талантами в быстрорастущей компании.

Как вы помогаете инженерам развиваться технически, когда команда работает в режиме высокой операционной нагрузки и сжатых сроков?

Оценка навыков обеспечения надежности (SLA), которые являются приоритетом для этой роли.

Какие метрики и практики мониторинга вы считаете обязательными для систем агрегации, от которых зависит безопасность клиентов в реальном времени?

Проверка умения взаимодействовать с другими отделами (Data Science, Product).

Опишите случай, когда требования продуктовой команды или дата-сайентистов конфликтовали с технической стабильностью системы. Как вы разрешили этот конфликт?

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abnormalsecurity
Страна
США
Зарплата
187 400 $ – 269 500 $