What you will do

Architect & Scale: Design and maintain high-throughput detection systems and backend services, ensuring low latency and high reliability.
Data Orchestration: Lead the development of robust data pipelines using Spark and Airflow to supply detection teams with high-fidelity data for ML model training and evaluation.
Technical Leadership: Partner with Engineering Managers to define technical roadmaps, mentor junior/mid-level engineers, and drive best practices in code quality and system design.
AI-Driven Innovation: Lead the team in adopting AI productivity initiatives, leveraging tools like Claude, OpenAI, and GitHub Copilot to accelerate the development lifecycle and automate internal workflows.
Cross-functional Collaboration: Work closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business needs into scalable technical solutions.
Operational Excellence: Manage and optimize cloud-native infrastructure on AWS/EKS, ensuring systems are cost-effective, secure, and performant.

Must Haves

8+ years of professional experience: Proven track record in production-level backend development with Python or Golang.
Data Engineering Expertise: Expert-level proficiency in building and optimizing distributed data pipelines using Spark and Airflow (or equivalent orchestration tools).
Cloud & Infrastructure: Extensive experience managing and scaling cloud-native applications on AWS (highly preferred), GCP, or Azure, with a proven track record of hands-on container orchestration using EKS.
Leadership & Mentorship: Experience leading technical projects, mentoring engineers, and contributing to the long-term technical strategy of a team.
System Design: Strong ability to design complex integrations and handle significant throughput/latency challenges.
Problem Solving: A methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale systems.
Database Proficiency: Strong experience with Postgres or similar relational databases at scale.
Education: BS in Computer Science, Applied Sciences, or a related engineering field.

Nice to Haves

Frontend Literacy: Familiarity with React and TypeScript to assist with internal tool visualizations.
Data Ecosystems: Experience with Databricks, Snowflake, or similar data lakehouse architectures.
Cybersecurity Domain: Background in threat detection, network security, or fraud prevention.
Advanced Degrees: MS in Computer Science or Electrical Engineering.

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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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