We are looking for a Senior Cyber Hygiene Automation Engineer to join a high-impact Business Information Security team. This role focuses on driving automation across cyber hygiene processes, improving real-time visibility, and strengthening overall security posture.
You’ll work at the intersection of security, automation, and data, with opportunities to explore AI/ML-driven enhancements in detection and response.
Key Responsibilities
- Design and build automation scripts and playbooks (Python, PowerShell) to monitor:
- Patch compliance
- Endpoint security health
- Configuration baselines
- Access controls
- Integrate security tools such as:
- Vulnerability scanners
- EDR platforms
- CMDB systems
- Develop APIs and integrations to unify data across tools and build centralized dashboards
- Drive transition from manual checks → real-time, event-driven monitoring
- Work with SOAR platforms or custom automation frameworks
- Explore and implement AI/ML use cases, including:
- Predictive risk modeling
- Anomaly detection
- NLP for prioritization of remediation
- Perform root cause analysis on recurring security issues
- Maintain documentation, runbooks, and architecture artifacts
Required Qualifications
- Bachelor's degree in Computer Science, Information Security, or a related technical field, or equivalent practical experience.
- 5+ years of experience in Information Security, with a focus on Security Operations, GRC, or Security Engineering.
- Strong programming/scripting proficiency (e.g., Python, Go, PowerShell) and experience with version control systems (Git).
- Hands-on experience integrating security tools via APIs (REST, SOAP).
- Demonstrable experience with public cloud platforms (AWS, Azure, or GCP) security controls and automation (e.g., Terraform, CloudFormation).
- Solid understanding of common cyber hygiene domains (Vulnerability Management, Configuration Management, Identity and Access Management, EDR health).
Nice to Have
- Experience with SOAR tools (Splunk Phantom, Palo Alto XSOAR)
- Exposure to AI/ML in security use cases
- Familiarity with frameworks like NIST, ISO 27001, CIS Benchmarks
- Experience with Splunk, Elastic, or security data lakes
- Certifications like CISSP, GCIH, or cloud security certs