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 characteris