Senior Security Research Engineer

Overview

We are looking for a Senior Security Research Engineer who will help drive Exabeam’s R&D efforts by distilling threat research, attacker tactics, techniques, and procedures into actionable intelligence for our New Scale Analytics Platform.

Opportunity

Exabeam is redefining how security operations teams detect, investigate, and respond to modern threats through behavioral analytics, AI, and intelligent automation. Reporting to the Security Research Manager, this is a senior individual contributor role focused on hands-on technical leadership, deep threat research, detection engineering, behavioral analytics, and cross-functional influence.

Responsibilities

• Serve as a senior technical contributor for Exabeam Security Research, helping shape direction for detection engineering, behavioral analytics, and threat research.
• Lead research into emerging attacker tactics, techniques, procedures (TTPs), and adversary behaviors across enterprise, cloud, identity, and SaaS environments.
• Design, develop, validate, and maintain high-fidelity detections, behavioral models, and analytics for the Exabeam platform.
• Act as a subject matter expert on the analytics engine, driving improvements to behavioral analytics, model quality, detection coverage, and accuracy.
• Develop security content that leverages the full Exabeam platform, including behavioral analytics, UEBA, search, automation, investigation workflows, and detection engineering capabilities.
• Continuously evaluate new attack techniques and validate detection efficacy through research, simulation, purple teaming, adversary emulation, and lab testing.
• Perform hands-on threat research, malware analysis, incident analysis, detection tuning, and content validation where appropriate.
• Collaborate closely with Product Management, Engineering, AI, and Customer Success teams to translate emerging threats into product capabilities and customer value.
• Contribute to technical thought leadership through blogs, conference presentations, webinars, whitepapers, and community engagement.
• Apply AI and Large Language Models (LLMs) to improve Security Research workflows, detection development, and research productivity.
• Identify opportunities to improve researcher productivity through AI-assisted research, detection development, testing, documentation, and content generation.
• Develop processes and guardrails for responsible use of AI in research workflows while maintaining detection quality and accuracy.
• Partner with Exabeam AI teams to evaluate emerging AI capabilities and incorporate them into research operations.
• Improve speed-to-market for new detections through automation, AI-assisted engineering, and repeatable development processes.
• Technical Influence & Mentorship
• Mentor and guide Security Researchers and Detection Engineers through technical reviews, research collaboration, and knowledge sharing.
• Help shape research priorities and technical execution plans in partnership with the Security Research Manager and cross-functional stakeholders.
• Provide technical coaching and feedback to raise the quality, scalability, and consistency of research outputs and detection content.
• Foster a culture of technical excellence, innovation, collaboration, and continuous learning through influence rather than direct people management.
• Balance strategic research initiatives with hands-on execution to ensure timely delivery of high-quality detections, analytics, and product improvements.
• Coordinate technical work across Engineering, Product Management, Threat Intelligence, Customer Success, and AI teams to translate research into customer value.
• Measure and communicate technical impact through meaningful metrics around detection coverage, quality, innovation, and delivery.

Qualifications

• 7+ years of experience in cybersecurity with significant expertise in threat detection, security research, threat intelligence, detection engineering, incident response, or related disciplines.
• Experience providing technical leadership, mentoring, or guidance to highly technical engineering or security research teams without requiring direct people-management responsibility.
• Deep understanding of modern attacker methodologies including MITRE ATT&CK, identity attacks, endpoint threats, cloud attacks, insider threats, and lateral movement techniques.
• Demonstrated experience developing high-quality security detections, behavioral analytics, correlation rules, or detection content for enterprise security products.
• Strong understanding of UEBA, SIEM, behavioral analytics, and detection engineering principles.
• Hands-on experience writing production-quality code and automation using Python and related scripting languages.
• Experience working with large-scale security telemetry including endpoint, identity, cloud, authentication, network, SaaS, and infrastructure logs.
• Experience working with APIs, automation frameworks, and modern development workflows.
• Strong analytical skills with the ability to evaluate detection quality, reduce false positives, and improve behavioral fidelity.
• Excellent written and verbal communication skills with experience presenting technical concepts to both executive and technical audiences.
• Proven ability to influence cross-functional partners and contribute to technical strategy through expertise, collaboration, and clear communication.

Preferred

• Hands-on experience with the Exabeam platform and a deep understanding of the BEAM analytics engine.
• Experience building behavioral models, machine learning features, or advanced detection logic.
• Practical experience leveraging Generative AI, LLMs, agentic workflows, or AI-assisted development to improve engineering productivity and research effectiveness.
• Experience with cloud platforms including AWS, Azure, and Google Cloud Platform.
• Knowledge of identity providers such as Microsoft Entra ID, Okta, Active Directory, and hybrid identity environments.
• Experience with Elasticsearch, SQL, Splunk, Kusto, or similar search and analytics technologies.
• Familiarity with CI/CD, automated testing, and content validation pipelines.
• Experience with malware analysis, reverse engineering, digital forensics, or incident response.
• Previous experience contributing to open-source security projects, research publications, conference presentations, or industry working groups.

Nice to Have

• Experience developing machine learning or behavioral analytics for cybersecurity applications.
• Familiarity with AI safety, evaluation, or prompt engineering techniques.
• Security certifications such as CISSP, GREM, GCIH, GCFA, GPEN, OSCP, OSCE, GXPN, or equivalent.
• Experience working in a commercial cybersecurity product organization.