Senior Software Engineer

Job Summary

We are seeking a Senior Software Engineer to join our Threat Detection Platform team and help build the next generation of malware detection and analysis technologies. This role focuses on developing scalable cloud-based services that analyze, classify, and process suspicious files using a combination of static analysis, dynamic analysis, and machine learning techniques.

Responsibilities

• Develop, optimize, and maintain static analysis capabilities, including PE and Authenticode signature validation, YARA scanning, Office macro analysis, PDF inspection, archive analysis, and cloud-based hash reputation lookups.
• Manage the machine learning inference pipeline across both products, including model integration, tuning, deployment, and version control within production services.
• Own and enhance the dynamic analysis environment, including Windows VM lifecycle management on KVM/libvirt, guest configuration, behavioral telemetry collection, and support for additional operating systems.
• Read, troubleshoot, enhance, and maintain C/C++-based analysis components that support platform detection capabilities.
• Improve detection effectiveness by developing new analysis engines, expanding file-type coverage, creating behavioral signatures, and increasing test coverage across detection workflows.
• Investigate and resolve production detection issues, including false positives, false negatives, engine failures, and sandbox-related issues.
• Participate in architectural discussions, design reviews, and code reviews to help maintain high engineering standards.
• Collaborate closely with cross-functional teams to continuously improve platform performance, reliability, and detection accuracy.

Requirements

• Minimum of 8 years of software engineering experience with a Bachelors degree in Computer Science, Engineering, or a related field; alternatively, 6+ years with a Masters degree, 3+ years with a PhD, or equivalent professional experience.
• Strong Python development experience, including multithreaded programming and performance optimization.
• Working proficiency in C and C++, with the ability to read, debug, build, and modify compiled analysis components.
• Solid understanding of static file analysis techniques, including PE file structures, code-signing validation, YARA rules, Office macros, PDF formats, and archive file inspection.
• Experience deploying and maintaining machine learning inference solutions in production using frameworks such as PyTorch, LightGBM, scikit-learn, or ONNX, including feature engineering and model optimization.
• Familiarity with KVM/libvirt or similar virtualization technologies and a working knowledge of Windows internals, or the ability to quickly develop expertise in these areas.
• Experience with malware analysis, sandbox technologies, threat detection platforms, or cybersecurity software.
• Comfortable working in Linux environments, including process troubleshooting, log analysis, and shell scripting on Ubuntu or Debian-based systems.
• Strong written communication skills and the ability to collaborate effectively within a distributed, asynchronous team environment.

Cross-Team Coverage Expectations

• Contribute to a collaborative engineering environment where team members provide coverage across functional areas when needed.
• Provide maintenance-level support and first-line incident response outside primary areas of expertise, including Python-based services, distributed task processing systems, management APIs, and deployment infrastructure.
• Support operational continuity during teammate absences and partner with subject matter experts when deeper technical specialization is required.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.