Abnormal - Senior Software Engineer Tech Lead Message Security Detection
Requirements
• 8+ years of professional experience: Proven track record in production-level backend development with Python or Golang. • Python or Golang • Data Engineering Expertise: Expert-level proficiency in building and optimizing distributed data pipelines using Spark and Airflow (or equivalent orchestration tools). • Data Engineering Expertise: • Spark and Airflow • 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. • Cloud & Infrastructure: • AWS (highly preferred) • proven track record of hands-on container orchestration using EKS • System Design: Strong ability to design complex integrations and handle significant throughput/latency challenges. • System Design: • Problem Solving: A methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale systems. • Problem Solving: • Database Proficiency: Strong experience with Postgres or similar relational databases at scale. • Database Proficiency: • Education: BS in Computer Science, Applied Sciences, or a related engineering field. • Education: • Frontend Literacy: Familiarity with React and TypeScript to assist with internal tool visualizations. • Frontend Literacy: • React and TypeScript • Data Ecosystems: Experience with Databricks, Snowflake, or similar data lakehouse architectures. • Data Ecosystems: • Databricks • Cybersecurity Domain: Background in threat detection, network security, or fraud prevention. • Cybersecurity Domain: • Leadership & Mentorship: Experience leading technical projects, mentoring engineers, and contributing to the long-term technical strategy of a team. • Leadership & Mentorship: • Advanced Degrees: MS in Computer Science or Electrical Engineering. • Advanced Degrees: • A note on AI in our process: Abnormal AI uses AI-assisted tools to help our recruiting team prepare for candidate interviews. These tools analyze resume content and role requirements to suggest interview questions and areas for the interviewer to explore.They do not make hiring decisions or screen candidates automatically. Every decision about a candidacy is made by a person. Further, if your application is successful and Abnormal AI makes a conditional offer of employment, we will carry out pre-employment checks which must be successfully completed to progress to a final offer. All processes and pre-employment checks are in line with prevailing legislation and Abnormal AI's policies relevant to our security and privacy standards. • A note on AI in our process:
Responsibilities
• Architect & Scale: Design and maintain high-throughput detection systems and backend services, ensuring low latency and high reliability. • Architect & Scale: • 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. • Data Orchestration: • Spark and Airflow • 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. • Technical Leadership: • 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. • AI-Driven Innovation: • AI productivity initiatives • Cross-functional Collaboration: Work closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business needs into scalable technical solutions. • Cross-functional Collaboration: • Operational Excellence: Manage and optimize cloud-native infrastructure on AWS/EKS, ensuring systems are cost-effective, secure, and performant. • Operational Excellence: • AWS/EKS
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