Staff Security Engineer - AI Security & Platforms

Ridgeline•Reno, NV

10h•Onsite

About The Position

Ridgeline is building a new AI Security & Platforms team focused on secure AI enablement for the business. This team will be responsible for building the platforms that support safe AI adoption and staying current with how AI is used, the security issues that emerge, and how to prevent them. As a Staff AI Security Engineer, you will own this space at a technical-leadership level. You will architect secure-by-default AI platforms, lead on AI/LLM threat security, partner with teams to embed security into how they build and use AI, and enforce the organization's standards for responsible, secure AI use. The ideal candidate will have strong skills in application security, cloud security, or security-focused software development, combined with significant depth in AI. Ridgeline values ownership, transparency, and a bias toward action, fostering a culture of growth, collaboration, and accountability.

Requirements

8+ years in application security, cloud security, or security-focused software engineering, including leading complex cross-functional initiatives.
Demonstrated depth in at least one of: secure code review and product security; cloud and infrastructure security (AWS, IAM, guardrails, policy-as-code); or building production software with a strong security focus.
Advanced proficiency in at least one high-level language (Python strongly preferred; Kotlin or TypeScript a plus).
Hands-on, daily use of AI/LLM tooling, the ability to engineer systems that use it, and the judgment to validate AI output for correctness and risk.
Applied experience securing or building AI/LLM-powered systems, or a clear track record of getting deep in a new technical domain quickly.
Sound architectural judgment, a habit of driving findings to systemic remediation, and honest risk calibration.
Strong written and verbal communication skills, with the ability to explain security tradeoffs clearly to engineers, product partners, and leadership.
Must be work authorized in the United States without the need for employer sponsorship.

Nice To Haves

Hands-on experience with prompt-injection prevention, LLM input/output sanitization, or agent / tool-use / MCP security.
Experience building developer platforms or security guardrail frameworks that scale across an organization.
Contributions to AI security research, open source security tooling, or emerging AI security standards.
Familiarity with cloud-native security at scale (AWS) and infrastructure-as-code (e.g., Terraform).

Responsibilities

Architect and build the platforms, guardrails, and reusable frameworks that enable safe and scalable AI adoption at Ridgeline, implementing secure-by-default patterns.
Identify and mitigate AI-specific risks such as prompt injection, model input/output sanitization, data leakage, and trust-boundary violations.
Secure agentic and tool-use systems, including function/tool calling and MCP server integrations, ensuring clear trust boundaries and least-privilege patterns.
Establish and operate guardrails for internal AI developer tooling to facilitate rapid development without compromising security.
Threat model new AI features and infrastructure to define security requirements proactively, collaborating with engineering and product teams.
Build AI-augmented security tooling and pipelines to enhance team capacity and maintain low false positive rates.
Set organizational standards for responsible and secure AI use, risk acceptance, and model/vendor evaluation.
Influence AI security decisions across engineering organizations through technical credibility.
Mentor engineers and establish team standards for effective and responsible AI use.
Utilize AI daily in personal work, build AI-powered systems, and validate AI output for correctness and risk.