Senior Platform Engineer – Secure AI DevSecOps

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As a Senior Platform Engineer – Secure AI DevSecOps, you will design, build, integrate, and operate enterprise-scale security platforms that support secure software development and AI-powered solutions. Working closely with Cybersecurity, Platform Engineering, and application development teams, you will embed security into developer workflows, automate security processes, and improve visibility across the software development lifecycle.
This role offers a unique opportunity to shape Ford's next generation of AI security and DevSecOps capabilities while enabling engineering teams to build secure, scalable, and innovative solutions.

Engineer, integrate, and operate AI Security and DevSecOps platforms supporting secure software delivery.
Build scalable security capabilities that improve automation, operational efficiency, and developer productivity.
Integrate security controls into developer workflows, CI/CD pipelines, and engineering platforms.
Develop self-service capabilities, onboarding experiences, and developer enablement resources.
Perform platform administration, upgrades, monitoring, troubleshooting, optimization, and production support.

Engineer and support AI-powered code security solutions and emerging AI security technologies.
Enable secure AI development practices across AI applications, agents, LLM-powered systems, and AI integrations.
Improve security visibility through dashboards, metrics, reporting, and operational insights.
Support vulnerability remediation through enhanced developer workflows and automated feedback mechanisms.

Implement and support security capabilities including:

Innovation

Evaluate emerging security technologies and drive successful proof-of-concepts into enterprise adoption.
Continuously improve the reliability, scalability, and usability of security platforms.

Required Qualifications

Bachelor's degree in Computer Science, Software Engineering, Cybersecurity, or a related technical field.
8+ years of experience in Platform Engineering, DevSecOps, Application Security, or Cybersecurity Engineering.
Proven experience designing, implementing, and operating enterprise-scale security platforms.
Strong understanding of:
- Secure Software Development Lifecycle (SSDLC)
- DevSecOps practices
- Developer workflows and platform engineering
Strong scripting and automation experience using:
- Python
- PowerShell
- Shell Scripting
- Similar programming languages
Experience integrating security solutions into CI/CD pipelines and enterprise developer platforms.
Hands-on experience with:
- GitHub Enterprise, GitHub Actions, GitLab CI/CD, Azure DevOps, or Tekton
- Kubernetes and container platforms
- Terraform and Infrastructure as Code
- Public cloud platforms (Azure, AWS, or GCP)
Knowledge of application security concepts including SAST, SCA, secrets management, and software supply chain security.
Strong communication and stakeholder management skills.
Ability to translate security requirements into scalable engineering solutions.

Preferred Qualifications

Experience with AI security technologies and platforms such as:
- Microsoft MDASH
- Google CodeMender
- Cycode
- Wiz Code
- SonarQube
- FOSSA
- Similar AI-assisted security solutions
Experience securing:
- Large Language Models (LLMs)
- AI Agents
- Retrieval-Augmented Generation (RAG) systems
- AI-integrated enterprise applications
Experience with AI governance and secure AI development practices.

Preferred Certifications

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