Cybersecurity Senior Engineer | AI Security

The Home Depot•GEORGIA - VIRTUAL - GA01, GA

4d•$120,000 - $180,000

About The Position

The Cybersecurity Senior Engineer advises on the security posture of AI models, AI bills of materials (AI-BOM), and SaaS agents at The Home Depot, from pre-production scanning through post-production remediation. The role guides teams deploying and operating AI-BOM, AI Security Posture Management (AI-SPM), and AI SaaS agent security controls. It advises on policies that gate risky models before release and on maintaining a complete enterprise inventory of models, agents, apps, and MCP servers. The role also establishes a program to classify third-party AI SaaS apps as approved or unapproved and expedite their threat modeling. The engineer designs automation workflows and capabilities for data collection, investigation, and incident response; develops threat-hunting and data-analysis strategies; identifies approaches to detecting malicious activity; and builds, configures, maintains, and monitors cybersecurity threat-defense capabilities and user-access management. Responsibilities include advising on model scanning and inventory, AI-BOM tracking, agent security tooling and policies, Shadow AI discovery, application-level troubleshooting, and documentation of standards, runbooks, policies, and exceptions. The position typically reports to a Manager or Senior Manager and has no direct reports. No travel is required. Work is primarily in a comfortable indoor area, mostly seated, with frequent opportunities to move about and rare need to move or lift light articles. Candidates must be at least 18 and legally permitted to work in the United States. Minimum education is a high school diploma and/or GED; minimum work experience is three years. The listed pay range for specified locations is $120,000 to $180,000.

Requirements

Must be at least 18 years of age.
Must be legally permitted to work in the United States.
Minimum of 3 years of work experience.
High school diploma and/or GED.

Nice To Haves

5+ years of hands-on experience in data security and/or application security, including engineering and administering security tooling in an enterprise environment.
Working knowledge of AI and ML model development, training, packaging, and deployment, including common model formats and registries and related risks such as unsafe serialization, poisoned or tampered models, and exposed secrets.
Experience advising engineering teams on security tooling and policy, including AI-BOM, AI-SPM, or comparable software supply chain and posture management practices.
Experience with CI/CD pipelines and release processes, including integrating security scanning and policy gates and deploying security products.
Experience troubleshooting security tools and integrations at the application level with engineering and platform teams.
Experience building and maintaining inventories and dashboards for assets such as models, applications, agents, and APIs, and driving findings to remediation against defined SLAs.
Experience working across multiple teams, with strong written and verbal communication skills.
Strong documentation skills, including policies, standards, runbooks, and intake procedures.
Ability to use AI tools to improve scripting, analysis, documentation, and operational efficiency while maintaining appropriate data protection and accuracy.
Experience with model scanning, SaaS security posture, SBOM or AI-BOM tooling, or third-party risk and threat-modeling programs.
Previous experience leading, coaching, or mentoring team members.

Responsibilities

Design automation workflows and capabilities supporting data collection, investigation, and incident response.
Develop threat-hunting and data-analysis strategies and capabilities.
Identify and propose technologies, methodologies, and approaches for detecting malicious activity.
Use indicators to scope and proactively respond to emerging threats.
Design, build, configure, maintain, and monitor cybersecurity threat-defense capabilities and user-access management.
Act as the advisory engineer for AI-BOM, AI-SPM, and AI SaaS agent security.
Advise on pre-production model scanning in CI/CD pipelines, including policies to block or flag risky models and maintaining a complete model inventory.
Advise on post-production scanning of running models and remediation of high- and critical-severity findings within defined SLAs.
Advise on inventorying and tracking the models, datasets, libraries, and dependencies behind each AI system.
Advise on SaaS agent security tooling across AI platforms, including policies and a complete agent inventory.
Classify third-party AI SaaS apps as approved or unapproved and build a repeatable threat-modeling and security-policy program for those apps.
Advise on a Shadow AI dashboard that discovers models, apps, agents, and MCP servers.
Troubleshoot application-level issues with engineering and platform teams.
Document standards, runbooks, policies, and exceptions.