Senior Engineer, AI Security

New York Technology Partners; Plano (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

New York Technology Partners seeks a hands-on Senior Engineer to lead AI security, platform modernization, and developer productivity for a large enterprise technology organization in Plano, Texas.

You will drive secure adoption of AI, build an AI-focused vulnerability management program, and enable rapid release of fixes when new threats emerge, while improving engineering efficiency with AI tooling and modernization.

Qualifications

• 10+ years in software or systems engineering.
• Strong background in application security and AI security.
• Proven experience rolling out AI developer productivity tools at scale (e.g., Copilot, Claude Code).
• Deep systems engineering expertise and experience architecting complex platforms.
• Experience leading large-scale vulnerability remediation efforts.

Responsibilities

• Enable AI adoption safely with guardrails and policies.
• Run AI vulnerability management and remediation roadmap.
• Ship rapid security fixes to emerging threats and risks.
• Improve developer productivity with AI-assisted workflows and tooling.
• Modernize the platform with Java modernization and upgrades.
• Strengthen CI/CD and DevSecOps pipelines to embed security.
• Architect, mentor, and influence engineering standards across teams.

Skills

Software engineering

Systems engineering

AI security

GitHub Copilot

Claude Code

CI/CD

DevSecOps

Kubernetes

Terraform

Ansible

Observability

SRE practices

Tools

GitHub Copilot

Claude Code

Terraform

Ansible

Kubernetes

Job description

We're looking for a hands-on Senior Engineer with deep systems engineering expertise to lead AI security, platform modernization, and developer productivity for a large enterprise technology organization. You'll drive the secure adoption of AI across engineering, build an AI-focused vulnerability management and remediation program, and make it possible to release fixes quickly when new security threats emerge.

This role combines technical leadership, architecture, and hands-on building. You'll set direction and also write the code and pipelines that improve engineering efficiency, strengthen security posture, and speed up software delivery.

Key Responsibilities

• Enable AI adoption safely. Lead secure adoption of AI capabilities, including LLM integrations and AI coding assistants such as GitHub Copilot and Claude Code, and define the guardrails, policies, and patterns that go with them.
• Run AI vulnerability management. Build and own the roadmap for managing vulnerabilities, including remediating findings surfaced by advanced AI security models (e.g., Mythos-class tools).
• Ship security fixes fast. Build rapid-release capabilities so the team can respond quickly to emerging security threats and platform risks.
• Improve developer productivity. Roll out AI-assisted engineering workflows and build custom tooling, such as Claude skills and Copilot extensions, that accelerate delivery.
• Modernize the platform. Lead Java modernization and platform upgrades across legacy and cloud-native systems.
• Build security into delivery. Strengthen CI/CD and DevSecOps pipelines so security is part of the software delivery lifecycle rather than an afterthought.
• Act as technical leader. Architect, mentor, and influence engineering standards across teams.

Required Qualifications

• 10+ years in software or systems engineering, with significant hands-on experience.
• Strong background in application security and AI security, including securing LLM integrations.
• Proven experience rolling out AI developer productivity tools such as GitHub Copilot or Claude Code at scale.
• Deep systems engineering expertise and experience architecting complex platforms.
• Experience leading large-scale vulnerability remediation efforts.

Preferred Qualifications

• CI/CD, DevSecOps, and secure SDLC practices.
• Cloud platforms (AWS, Azure, or GCP) and Kubernetes.
• Infrastructure automation (Terraform, Ansible, or similar).
• SRE practices and observability tooling.