Senior Software Engineer - Message Security Detection

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Skills you'll use

What you'll 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.
• 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).

Who can apply

• 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 .
• 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.

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