Barracuda is a company dedicated to making the world a safer place through cloud-enabled security solutions. They are looking for a Security Automation Engineer responsible for engineering the Barracuda XDR SOAR platform, conducting R&D efforts, and executing offensive security operations to enhance threat detection and response capabilities.
Responsibilities:
- Engineering the Barracuda XDR SOAR solution
- Sprint tasks within the SOC Agile Sprint cycle to continuously improve overall SOC maturity level and R&D efforts
- Develop and maintain documentation on new processes, tools, technologies, and on-going R&D efforts
- Integrating various APIs into the SOC tech stack
- Proactive threat hunting amongst partners' networks to identify malicious activity
- Attack and Defend activities to test current detections and develop new detections
- Ensuring MITRE ATT&CK Framework coverage is obtained by XDR detections
- Conduct threat intelligence research
- Train new and current cyber security analysts on existing or new technologies, new or existing processes
- Will be on a rotating 24x7x365 on-call schedule to investigate, triage, and help customers remediate active breaches/incidents
- Designing and implementing AI-driven security automations, including Agentic AI workflows to autonomously investigate, triage, and respond to alerts
- Building and maintaining Retrieval-Augmented Generation (RAG) pipelines to enhance threat intelligence enrichment, alert context, and analyst decision-making
- Developing and integrating AI agents with SOC tooling (SIEM, SOAR, EDR) to reduce manual effort and improve response times
- Leveraging LLMs and AI frameworks to automate repetitive SOC tasks such as alert analysis, ticket generation, and incident summarization
- Integrating and managing MCP servers and agent orchestration frameworks to enable scalable, modular AI-driven workflows
- Experimenting with and operationalizing machine learning models for anomaly detection, alert prioritization, and signal-to-noise improvement
- Driving R&D initiatives focused on applying Generative AI in cybersecurity, including detection engineering, threat hunting, and purple team exercises
- Building internal tools and prototypes that combine security data pipelines with AI capabilities to improve SOC efficiency and accuracy
Requirements:
- 4-5 years prior cybersecurity or SOC experience
- Bachelor's degree or Masters Degree in Cyber Security or Information Security or related field experience
- CIH, CEH, CompTIA Network+ or Security+, or other relevant certification
- Experience working with various SOC tools including SIEM, SOAR EDR, email protection, sandboxes, ticketing systems, etc
- Expertise with analyzing attack advanced cyber vectors such as ransomware, Business Email Compromise etc
- Experience responding to active security threats and incidents
- Experience with cloud tools such as AWS, Azure and GCP
- Experience working with APIs
- Experience troubleshooting in a technical environment, analytical, problem-solving skills with SOAR platform
- Customer service experience
- Experience with threat intelligence research, IOC gathering, and threat hunting
- Understanding of cybersecurity framework such as NIST, MITRE ATT&CK, etc
- Fundamental understanding of corporate IT environments, including networking, cloud infrastructure, etc
- Excellent verbal and written communication skills
- Hands-on experience building or working with Agentic AI systems, including multi-step autonomous workflows and tool-using agents
- Experience implementing RAG architectures, including vector databases, embeddings, and context retrieval strategies
- Familiarity with LLMs (e.g., OpenAI, open-source models) and their application in cybersecurity use cases
- Experience integrating AI into production environments, including API orchestration and automation pipelines
- Exposure to MCP servers, agent frameworks, or similar orchestration systems for managing AI-driven workflows
- Strong understanding of how to apply AI/ML to security operations problems such as alert fatigue, threat detection, and incident response
- Ability to evaluate and tune AI outputs for accuracy, reliability, and security relevance in a SOC environment