Security Control Engineering

Key ResponsibilitiesSecurity Control Engineering

• Deploy, configure, and maintain core security platforms including EDR, email, service edge, cloud security posture management, and identity controls.
• Design control rollouts that account for coverage gaps, exception handling, impact, and rollback.
• Integrate security tooling with IT and engineering systems so data flows are usable, not just collected.
• Own control health monitoring: agent coverage, policy failed enforcement, and failure detection.

Cloud and Infrastructure Security

• Implement and maintain guardrails across AWS, Azure, and GCP, including preventative posture monitoring, and remediation workflows.
• Build and maintain hardened baselines for operating systems, containers, and cloud services aligned to CIS or equivalent benchmarks.
• Engineer secrets management, key management, and certificate lifecycle controls in partnership with platform teams.
• Support secure network design implementation including segmentation, egress control, and remote access.

Automation and Engineering Practice

• Automate repetitive security operations work through scripting, APIs, and code.
• Treat security configuration as code: version control, peer review, testing, and repeatable infrastructure as code deployment.
• Build and maintain integrations between security, IT, and engineering systems so data flows without manual handling.
• Write and maintain documentation and runbooks good enough that someone else can operate what you built.

Operations Support and Remediation

• Support incident response with rapid control changes, containment actions, and forensic data collection.
• Partner with Vulnerability Management to isolate root causes for vulnerabilities, automated incident triage, and investigation ticket.
• Participate in an on-call rotation for security platform issues and high-severity incidents.
• Contribute to control evidence collection for audit and customer assurance activity.

AI/ML Security

• Implement security guardrails for internal AI/LLM systems, including protections against prompt injection, model poisoning, and unauthorized data exfiltration.
• Maintain and secure the enterprise AI infrastructure, ensuring secure configuration of AI and model serving environments.
• Monitor and audit AI usage, ensuring adherence to governance policies for non-human identities and autonomous agents.
• Stay current on emerging threats to AI systems and adapt security controls to defend against AI-assisted attack vectors.

Required Qualifications

• Experience: 5+ years in security engineering, infrastructure engineering with a security focus, or a closely related hands-on role.
• Platform Ownership: Demonstrated ownership of at least two enterprise security platforms end to end, including deployment, tuning, and ongoing operation.
• Cloud Expertise: Strong cloud security engineering experience with at least one major provider, including native security services and policy enforcement.
• Automation: Practical scripting and automation skills working against vendor APIs.
• Core Systems: Solid grounding in operating system internals, networking, and identity protocols such as SAML, OIDC, and OAuth.
• Practices: Experience supporting infrastructure as code and version-control workflows.
• Problem Solving: Troubleshooting discipline able to isolate root causes in complex environments without guessing.