Your Role:

We are seeking an AI Security Engineer to own the technical security controls for how Alpaca uses AI. The scope includes identity for AI agents and automations, security requirements for AI tools and integrations, guardrails, and security logging. You will also assist in developing AI-powered security tooling.

You will keep those controls consistent as AI adoption grows, and you will work with the teams building with AI so security is part of the design.

This role reports to the Enterprise Security Architect and works closely with AI Enablement, Engineering, DevOps, GRC, and the wider Security team.

The Security Team is 100% distributed and remote.

Things You Get To Do:

The core responsibilities of the AI Security Engineer are focused on AI access controls, secure AI platforms, guardrails, visibility into AI usage, and AI-powered security tooling.

AI Identity and Access Controls:

• Agent Identity: Define how AI agents, bots, and automations authenticate, what they can access, and how their actions are attributed and audited.
• Tool Access: Own security requirements for AI tool integrations, including least-privilege access and credential handling.
• AI Assistant Controls: Define and enforce security settings for approved AI tools, including data handling and access policy.
• Least Privilege: Limit each agent and integration to the access it needs, and review that access when the integration changes.

Secure AI Platform, Tooling, and Response:

• Security Requirements: Define security requirements for internal AI applications, including identity, data handling, secrets, and review of new integrations.
• Guardrails: Design and implement guardrails for AI applications and agents.
• Design Reviews: Review new AI applications and integrations for security risks, and give builders clear, practical requirements.
• Security Tooling: Assist Security Operations in developing AI-powered tooling that supports detection, investigation, and response work.
• Safe Use in Security: Apply the same identity, data handling, and logging requirements to security team AI tools as to the rest of the company.
• Telemetry Requirements: Define the security logging AI systems must produce, and work with Security Operations on detection.
• Approved Use: Maintain visibility into AI tool usage and confirm it follows approved configurations.
• Incident Support: Lead the AI-specific aspects of security incidents, such as agent misuse or data exposure through AI tools.
• On-Call: Participate in the Security Operations on-call rotation after onboarding and cross-training.

Governance:

• Standards: Turn AI security standards into technical controls.
• GRC Partnership: Partner with GRC on AI governance and provide technical evidence for control design.

Who You Are (Must-Haves):

• Excited about Alpaca’s mission and what we’re building
• 2+ years of experience in security engineering, application security, or cloud security roles
• Hands-on experience securing LLM applications, AI agents, or AI developer tools
• Understanding of AI-specific risks, such as prompt injection, data leakage, excessive agency, and insecure tool use (for example, the OWASP Top 10 for LLM Applications)
• Experience with identity and access controls for services and non-human identities, including OAuth, service accounts, and secrets management
• Programming experience in Python or another general-purpose language
• Experience with CI/CD security checks and cloud-native deployments
• Experience with security operations or incident response
• Strong written and verbal communication skills, especially when explaining risk to non-security builders
• Comfortable working cross-functionally and making pragmatic security decisions
• Willing to participate in an on-call rotation
• Experience building AI-assisted workflows for security operations
• Experience building security telemetry for AI systems

 Who You Might Be (Nice-to-Haves):  

• Experience securing financial, trading, or other highly regulated platforms
• Experience securing enterprise AI coding tools and AI integrations
• Experience with policy-as-code and Kubernetes
• Familiarity with AI governance frameworks, such as the NIST AI Risk Management Framework or ISO 42001
• Ability to balance security rigor with operational efficiency and business needs