Senior Software Engineer — Python exp is a must

SonicWall  is a cybersecurity forerunner with more than 30 years of expertise and is recognized as a leading partner-first company, ensuring our partners and their customers are never alone in the fight against cybercrime. With the ability to build, scale and manage security across the cloud, hybrid and traditional environments in real-time, SonicWall provides relentless security against the most evasive cyberattacks across endless exposure points for increasingly remote, mobile and cloud-enabled users. With its own threat research center, SonicWall can quickly and economically provide purpose-built security solutions to enable any organization—enterprise, government agencies and SMBs—around the world. For more information, visit  www.sonicwall.com  or follow us on  Twitter ,  LinkedIn ,  Facebook  and  Instagram .

Role 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.

Own the core detection capabilities across both platforms, including static and dynamic analysis engines, machine learning inference pipelines, compiled analysis components, and the Windows-based sandbox environment. Responsible for driving detection accuracy, platform reliability, and the evolution of analysis technologies that power threat verdicts.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 Bachelor’s degree in Computer Science, Engineering, or a related field; alternatively, 6+ years with a Master’s 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 prov…