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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Security Engineer - AI Security & Platforms - **Company:** Ridgeline, Inc. - **Location:** United States - **Experience:** Expert - **Salary:** $164,000.0 - $205,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Application Frameworks, Cloud Computing Security, Information Leak Prevention, Cursor (Graphical User Interface Elements), Identity and Access Management, Python (Programming Language), Open Source Technology, Secure Coding, Software Deployment, Software Engineering, TypeScript, Cloud Platform System, Large Language Models, Software Security, Kotlin, Build Management, AI Platforms, Production Code, Terraform - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/senior-security-engineer-ai-security-platforms-ridgeline-8802281 ## About the Role * 4+ years of experience in application security, cloud security, or security-focused software engineering, including owning projects independently and partnering across teams * Demonstrated depth in at least one of: secure code review and product security; cloud and infrastructure security (AWS, IAM, guardrails); or building production software with a strong security focus * Proficiency in at least one high-level language (Python preferred; Kotlin or TypeScript a plus) * Hands-on, daily use of AI/LLM tooling, and the judgment to validate its output for correctness and risk. This is essential to the role. * Applied experience securing or building AI/LLM-powered systems, or a clear track record of getting deep in a new technical domain quickly * A habit of driving findings to remediation rather than just reporting them, with honest risk calibration * Strong written and verbal communication, with the ability to explain security tradeoffs clearly to engineers and product partners Bonus: * Hands-on experience with prompt-injection prevention, LLM input/output sanitization, or agent / tool-use / MCP security * Experience building security automation, internal tooling, or guardrail frameworks * Familiarity with cloud-native security (AWS) and infrastructure-as-code (e.g., Terraform) * Contributions to AI security research, open source security tooling, or emerging AI security standards ## Description 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. The impact you will have: * 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 recognized expertise in one or more AI security areas (prompt-injection defense, agent/MCP security, internal AI tooling guardrails) and own coverage for that area * Use AI fluently every day to accelerate and scale your work, validating its output for correctness and risk ## Related Videos - [Kotlin Multiplatform - True power of native code reuse](https://www.wearedevelopers.com/videos/4-kotlin-multiplatform-true-power-of-native-code-reuse) - [Infrastructure as Code: The Developer's Secret Weapon](https://www.wearedevelopers.com/videos/1221-infrastructure-as-code-the-developer-s-secret-weapon) - [Do TypeScript without TypeScript](https://www.wearedevelopers.com/videos/327-do-typescript-without-typescript) - [Automated Security for the Entire SDLC](https://www.wearedevelopers.com/videos/100323-automated-security-for-the-entire-sdlc) - [Why Kotlin is the better Java and how you can start using it](https://www.wearedevelopers.com/videos/661-why-kotlin-is-the-better-java-and-how-you-can-start-using-it) - [The AI Security Survival Guide: Practical Advice for Stressed-Out Developers](https://www.wearedevelopers.com/videos/1015-the-ai-security-survival-guide-practical-advice-for-stressed-out-developers) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Dev Digest 196: AI Killed DevOps, LLM Political Bias & AI Security](https://www.wearedevelopers.com/magazine/659-dev-digest-196-ai-killed-devops-llm-political-bias-ai-security) - [Dev Digest 134 - Where pixels sing?](https://www.wearedevelopers.com/magazine/477-dev-digest-134-where-pixels-sing) - [Got AI ideas but no money? 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