Security Agent Engineer - Remote Eligible

Security Agent Engineer

Anvilogic is a Palo Alto-based AI cybersecurity startup founded in 2019 by security veterans and data scientists from Fortune 500 companies.

Our mission is to democratize threat detection and hunting for today's SOC teams to easily be done across hybrid, multi-clouds and security data lakes without needing to centralize data or rip and replace tools. Further, with our investments in AI-powered automation of detection-as-code to create, test, tune and deploy detections, SOC users can implement high-efficacy detection and hunting techniques without writing a single line of code nor manually wrangling data.

Anvilogic raised $45M Series C funding in April 2024 and is backed by top-tier VC firms and prominent industry executives. Anvilogic's AI-powered Multi-Data Platform SIEM is used by many of the industry's most advanced security teams.

Learn about our customers: anvilogic.com/customers

Job Description

As a Security Agent Engineer at Anvilogic, you are responsible for designing, building, and deploying AI-powered security agents that autonomously analyze complex cybersecurity data and support incident response workflows. You will combine deep cybersecurity expertise with cutting-edge AI/ML techniques to create intelligent systems that can detect, analyze, and respond to security threats at scale. Working with technologies such as LLMs, agentic frameworks, AWS, Azure, Snowflake, and various security data platforms, you'll build the next generation of autonomous security operations tools.

• Design, build, and deploy AI-powered security agents for threat detection, incident analysis, and automated response
• Develop agentic workflows that can autonomously perform log forensics, threat hunting, and incident response tasks
• Work with product management teams to translate cybersecurity operational requirements into agent capabilities and performance metrics
• Integrate security agents with existing data lakes, SIEM platforms, and security toolstacks
• Embed security practitioner knowledge and methodologies into agent decision-making processes
• Mentor engineering teams on cybersecurity best practices and agent development patterns
• Collaborate with security operations teams to validate agent outputs and refine detection logic