> Markdown version of [/jobs/ext/3976140-software-engineer-ai-security](https://www.wearedevelopers.com/jobs/ext/3976140-software-engineer-ai-security). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, AI Security - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Contract:** Permanent contract - **Skills:** Computer-Aided Design, Artificial Intelligence, Code Review, Cyber Security, Software Safety, Runbook, Secure Coding, Security Software, Software Deployment, Software Engineering, Software Systems, Large Language Models, Code Restructuring, Vulnerability Analysis - **Published:** October 27, 2026 - **Apply:** https://www.careerbuilder.com/job-details/software-engineer-ai-security-seattle-wa--603f16ac-b231-455e-8afc-95e513a31a06 ## About the Role Software Engineering, Artificial Intelligence (AI), Auditing, MCP - Microsoft Certified Professional, Computer Security, Artificial Intelligence (AI), Operations Security (OPSEC), Test Plan/Schedule, Security Software, Security Infrastructure ## Description We are building a first-of-its-kind vulnerability auditing and review platform for LLM and foundational model integrated software including components like foundational models, MCP servers, agents, and agent skills/capabilities. As an SDE 1 on this team, you will contribute to the design, development, testing, deployment, and operation of security-focused software systems that help identify and mitigate vulnerabilities across AI-integrated applications., Platform Development & Feature Delivery * Design, implement, test, deploy, and maintain security-focused features for the vulnerability auditing and review platform. * Build and extend vulnerability detection capabilities for LLM-integrated services and tools including foundational models, MCP servers, agents, and agent skills/capabilities. * Deliver working software features end-to-end, working backwards from customer requirements through production deployment and ongoing operations. * Refactor and deprecate existing systems as the platform evolves, ensuring long-term maintainability and extensibility. Security & AI Safety Engineering * Develop automated scanning and analysis tooling to identify security vulnerabilities in AI-integrated software components. * Implement detection mechanisms for adversarial attacks, prompt injection, capability boundary violations, and other LLM-specific threat vectors. * Collaborate with applied scientists to translate AI safety research into production-grade platform features. * Apply secure coding practices and threat modeling to all platform components. Operational Excellence * Own operational health of your features monitor, alarm, triage, and resolve production issues. * Identify root causes of operational failures and implement permanent fixes; never settle for the status quo. * Proactively identify and execute on opportunities to improve the team"s operational posture (automation, runbooks, telemetry, dashboards). * Make effective priority tradeoffs between new feature development and operational improvements. Design & Technical Leadership * Design software solutions that bring clarity to difficult problems with visible risks or roadblocks. * Participate actively in code reviews, providing meaningful and constructive feedback to engineers at all levels. * Document how the platform is constructed, tested, operated, and secured and how it fits into the broader AI safety ecosystem. * Keep skills current; evaluate and apply industry innovations in security, AI safety, and software engineering where applicable. Mentorship & Team Development * Actively mentor SDE 1s and new team members to accelerate their productivity and growth. * Train new teammates on platform architecture, operational practices, and team norms. * Contribute to hiring efforts through interviews, candidate assessments, and bar-raising. Collaboration & Communication * Work with customers, stakeholders, and peers (including applied scientists) to understand business and customer value and ensure the platform solves the right problems. * Resolve disagreements with peers through constructive, inclusive dialogue. * Communicate effectively about the work you deliver status, risks, tradeoffs, and outcomes.