At BeyondTrust, we’re on a mission to create a safer digital world through our leading cybersecurity SaaS portfolio. Our culture is built on trust, flexibility, and continual learning, empowering you to grow your skills, take ownership of impactful projects, and be recognized for meaningful results. You’ll work alongside experts who challenge, support, and inspire you every step of the way.
About the Role
We are seeking a Staff Research Engineer to drive innovation in our identity security platform by blending cutting-edge security research with scalable engineering practices. You’ll operate at the intersection of software development and cybersecurity research, transforming advanced threat insights into production-grade systems that safeguard global organizations from identity-based attacks.
Key Responsibilities
Research & Innovation
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Conduct original research to uncover emerging identity attack techniques and design novel detection methods.
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Develop rule-based analytics, behavioral detection, and machine learning models for threat identification.
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Expand large-scale entitlement graph systems to map privilege escalation and identity risks.
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Build proactive recommendation engines to detect and prevent security misconfigurations.
Engineering & Implementation
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Design and deploy secure, scalable systems focused on reliability and performance.
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Build and maintain detection pipelines using PySpark, Spark SQL, and distributed computing frameworks.
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Implement efficient data representations (graphs, time-series) to enhance analytical capabilities.
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Apply best practices in testing, automation, and CI/CD pipelines to ensure robust deployments.
Data Analysis & Optimization
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Analyze large-scale datasets using Spark and Databricks to validate detection hypotheses.
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Continuously refine algorithms using real-world telemetry and security performance data.
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Collaborate with data science teams to integrate machine learning models into live detection environments.
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Optimize data pipelines for scalability and performance across large environments.
Leadership & Collaboration
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Mentor engineers and researchers, fostering technical excellence within the team.
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Publish findings and represent BeyondTrust at industry conferences and security events.
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Work cross-functionally to align research insights with product strategy and roadmap priorities.
Qualifications
Required
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Strong engineering experience building and maintaining production security systems.
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Expertise in Python programming and SQL optimization.
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Hands-on experience with SIEM tools, log analysis, and detection systems.
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Understanding of adversarial tactics (TTPs) and defensive countermeasures.
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Background in event detection, alert tuning, and system optimization.
Preferred
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Experience with Apache Spark, Databricks, or other distributed data processing platforms.
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Security research background with published papers or conference presentations.
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Knowledge of cloud security, containerization (Docker, Kubernetes), and graph databases.
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Familiarity with machine learning in cybersecurity applications.
Technologies Used
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Required: Python, SQL, distributed data systems
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Preferred: PySpark, Databricks, graph databases, AWS/Azure/GCP, Docker, Kubernetes, ML frameworks
Why BeyondTrust
This is a unique opportunity to shape the future of identity security—bridging deep research with practical defense systems used by organizations worldwide. You’ll have the freedom to explore novel security challenges, engineer at scale, and share your expertise with the global cybersecurity community.
Our Commitment
BeyondTrust celebrates diversity, inclusion, and innovation. We hire exceptional people from all backgrounds and believe that when we are different together, we are stronger together.
About BeyondTrust
BeyondTrust is the global leader in identity security, protecting the entire Path to Privilege™ across cloud and on-premises environments. With more than 20,000 customers—including 75 of the Fortune 100—we’re trusted to help organizations neutralize threats, reduce risk, and streamline secure access. Learn more at www.beyondtrust.com.