Senior Security Engineer - AI Security & Platforms

About Ridgeline

Ridgeline is the industry cloud platform for investment management. It was founded by visionary tech entrepreneur Dave Duffield (co-founder of both People Soft and Workday) to apply his successful formula of solving operational business challenges with bold innovation and human connectivity to the unique needs of the investment management industry.

Location:

San Ramon, CA;
Reno, NV

Ridgeline is the industry cloud platform for investment management. It was founded by visionary tech entrepreneur Dave Duffield (co-founder of both People Soft and Workday) to apply his successful formula of solving operational business challenges with bold innovation and human connectivity to the unique needs of the investment management industry.

Ridgeline started with a clean sheet of paper and a deep bench of experts bound by a set of core values and motivated to revolutionize an industry underserved by its current tech offerings. We are building a new, modern platform in the public cloud, purpose-built for the investment management industry and we are prioritizing security, agility, and usability to empower business like never before.

With a growing campus in Reno and offices in New York, Lake Tahoe, and the Bay Area, Ridgeline is proud to have built a fast-growing, people-first company that has been recognized by Fast Company as a  Best Workplace for Innovators,  by The Software Report as a  Top 100 Software Company,  and by Forbes as one of  America's Best Startup Employers.

Are you a security engineer who wants to define what secure AI looks like for an entire company rather than chase it after the fact? Do you want to build the platforms and guardrails that let a business adopt AI quickly and safely, while keeping pace with emerging AI threats and how to defend against them? Are you already fluent with AI and treat it as core to how you build?

If so, we're standing up a new team and we invite you to help shape it.

Ridgeline is building a new AI Security & Platforms team focused on secure AI enablement for the business: building the platforms that support safe AI adoption, and keeping 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.

Because the domain is still young, we are looking for someone who has already shown strong skills in application security, cloud security, or security-focused software development, and who pairs that with real depth in AI.

At Ridgeline, the workplace culture is just as important as the products we build. We value ownership, transparency, and a bias toward action - which means we're always looking for solutions rather than just identifying problems. We're a team that chooses growth over comfort, owns our setbacks as much as our wins, and thrives on the kind of collaboration that pushes everyone to do their best work.

If that's the environment where you do your best work, we would be interested to meet you.

You must be work authorized in the United States without the need for employer sponsorship.

• Design and build the platforms, guardrails, and reusable frameworks that enable secure AI adoption in your area, owning automation projects end to end - from design through Infrastructure-as-Code deployment and operation
• Independently assess the security impact of AI-powered features and lead security reviews in the areas you support, identifying complex AI risks that generic tooling misses - prompt injection, input/output sanitization gaps, data leakage, and trust-boundary violations
• Design and implement least-privilege patterns and clear trust boundaries for agentic / tool-use systems and MCP integrations, rather than only applying existing ones
• Own and extend guardrails for internal AI developer tooling (e.g., Claude Code, Cursor), improving coverage as new risks and usage patterns emerge
• Threat model AI features and integrations in your area to define security requirements before they are built, partnering with engineering so the secure path is also the easy one
• Own triage and remediation tracking for AI-related findings in your area, driving SLA compliance, validating fixes, and using AI to accelerate root-cause analysis and variant detection across related findings
• Design and build AI-augmented security tooling and pipelines that multiply review capacity, writing production-quality code and reviewing peers' code and Infrastructure-as-Code for security correctness, while keeping false positives low enough that engineering trusts the results
• Act as the primary AI Security partner for multiple engineering teams, sought out for design input on new AI features rather than only post-hoc review
• Develop…