Senior Threat Researcher Detection Engineer (Romania)

**About Us** Sophos is a cybersecurity leader defending 600,000 organizations globally with an AI-driven platform and expert-led services. Sophos meets organizations wherever they are in their security maturity and grows with them to defeat cyberattacks. Its solutions combine machine learning, automation, and real-time threat intelligence with frontline human expertise from Sophos X-Ops to deliver advanced, 24/7 threat monitoring, detection, and response. Sophos offers industry-leading managed detection and response (MDR) alongside a comprehensive portfolio of cybersecurity technologies — including endpoint, network, email, and cloud security, extended detection and response (XDR), identity threat detection and response (ITDR), and next-gen SIEM. Together with expert advisory services, these capabilities help organizations proactively reduce risk and respond faster, with the visibility and scalability needed to stay ahead of evolving threats. Sophos goes to market with a global partner ecosystem, including Managed Service Providers (MSPs), Managed Security Service Providers (MSSPs), resellers and distributors, marketplace integrations, and cyber risk partners, giving organizations the flexibility to choose trusted relationships when securing their business. Sophos is headquartered in Oxford, U.K. More information is available at [](https://www.sophos.com). **Role Summary** We are seeking a detail-oriented and technically skilled Detection Engineer to join our X-OPS team. In this role, you will be responsible for analyzing advanced security threats—ranging from malware to complex web attacks—and translating threat intelligence into high-fidelity detections across our platform. Your work will help ensure our analysts and clients receive highly accurate, actionable alerts with minimal noise. You will leverage data from over 40 third-party and internal sources, partner with our CTU Threat Intelligence team, and use a range of scripting and automation tools to strengthen detection capabilities. The ideal candidate is a hands-on security practitioner with a deep understanding of endpoint behavior, malware analysis, and detection development who thrives in fast-paced, technical environments. ### What You Will Do - Develop countermeasures to detect advanced threats based on research and intelligence from the CTU team. - Analyze endpoint behaviors and logs to design detections using multi-source telemetry. - Continuously refine and monitor detection rules to optimize the signal-to-noise ratio for alerts. - Research and implement alert handling for new device ingestions, ensuring high-value signal delivery. - Leverage internal tooling to distinguish native from standard integrations for detection accuracy. - Collaborate on the development of internal tools, automation, and detection infrastructure. - Act as a subject matter expert across departments including Product Management, Marketing, and Labs Research. ### What You Will Bring - Strong passion for cybersecurity research and the ability to quickly learn emerging technologies. - Hands-on experience in scripting languages (PowerShell, Bash, Python) and use of Python data science libraries (e.g., NumPy, Pandas, Matplotlib). - Knowledge of CI/CD pipelines, testing frameworks, and automation principles. - Proficiency in analyzing logs from firewalls, proxies, and security infrastructure to identify anomalies. - Familiarity with event logs, traffic pattern anomalies, and threat hunting methodologies. - Strong understanding of endpoint detection, Linux/Unix and Windows OS internals, vulnerability identification, and workflow automation. - Experience with event correlation and incident reconstruction using log data is a plus. - Network traffic analysis skills, including identification of anomalous or malicious traits is a plus. - Solid grasp of database querying, systems architecture, and process automation for operational improvements is a nice to have. - **Desirable:** - Strong experience with XDR. - **Nice to have** - Experience in malware analysis, including static/dynamic techniques and reverse engineering (IA32/64, ARM binaries). - Forensic analysis of memory and disk images across various OS and file system types.