AI Security - Principal Security Research Engineer I - Elastic

Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.

What is The Role

As a Principal Security Research Engineer on the Threat Research and Detection Engineering (TRaDE) team, you'll play a key role in shaping the detection capabilities of Elastic Security. You'll work hands-on with detection engineering and threat research, focusing on enhancing our defenses, particularly in the areas of AI security. This position invites you to apply your solid security background and keen interest in validating detection methods, helping to create effective and reliable detection content that benefits the wider community.

What You Will Be Doing

Improving and creating new internal rule management capabilities to ship rigorous protections

Developing new capabilities and Elastic AI workflows to steer and streamline our threat research and detection engineering processes

Investigate new multidomain threat vectors and attack methodologies to stay ahead of emerging risks

Monitor security trends and threat intelligence reports for relevant insights

Create and present findings to enhance team knowledge and community awareness

What You Bring

We're looking for candidates with experience in Generative AI Security and intimately understand MITRE ATLAS / ATT&CK threat techniques and behaviors.

Experience with Elastic Security Solution and proficiency in writing or validating detections using a query language (e.g. EQL, KQL, SQL)

Demonstrated experience leveraging AI-assisted development tools to accelerate feature development, debug complex systems, optimize existing codebases, generating telemetry, conduct threat research, and assist detection engineering workflows.

Proven ability to seamlessly transition between different projects, codebases, or scrum teams based on dynamic business priorities.

You have a proven track record of using AI to accelerate development, debug complex systems, and optimize code, while still owning the final outcomes.

Proficiency in modern AI/ML frameworks and hands-on experience integrating LLM APIs into production applications

You work autonomously and can drive decisions and results in a distributed team by leveraging asynchronous, direct, and transparent communication.