Information Security Automation Engineer

Role Purpose

 

 

 We are seeking an Information Security Analyst and Automation Engineer  to support and advance our security posture across data- and AI-driven initiatives. This role is ideal for a security professional early to mid-career who is eager to work at the intersection of information security, data governance, and artificial intelligence. 

 

Key Responsibilities

 

 

• Support the design and creation of AI agents that enhance information security capabilities. 

• Create and maintain automated agents to handle mundane and repeatable security requests, such as: 

• Access and entitlement reviews 

• Evidence collection for audits and compliance 

• Policy guidance and security FAQs 

• Intake and triage of security questionnaires and risk assessments 

• Security documentation and reporting 

• Define and implement guardrails for AI agents, such as: 

• Role-based access controls and least-privilege permissions 

• Human-in-the-loop approvals for sensitive or high-risk actions 

• Logging, monitoring, and auditability of agent activity 

• Clear escalation paths when confidence thresholds or policy boundaries are exceeded 

• Collaborate with engineering, data, and AI teams to integrate AI agents into existing workflows 

• Mentor and hold learning sessions to ensure best practices are leveraged across Information Security.  

 

Experiences/Education - Required

 

 

• Bachelor’s degree in information security, Computer Science, Information Systems, Data Science, Engineering, or a related field, OR equivalent proven practical experience through relevant work, internships, bootcamps, or self-directed learning 

• 1–4 years of experience in the following areas: 

• Information security or cybersecurity 

• Cloud engineering in AWS and Azure, data engineering, or platform operations with security exposure 

• Agile, DevOps experience 

• AI programming experience 

• Hands-on experience supporting or securing: 

• Data platforms, analytics environments, or cloud infrastructure 

• APIs, applications, or internal tooling 

• Exposure to AI, machine learning, such as using and supporting AI/ML tools and platforms, building automations or AI-assisted workflows, participating in AI or data-related projects from a security perspective