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.

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.

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.

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 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.

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.

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.