AI Security Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Take charge of AI behavior monitoring: Determine the characteristics of trustworthy versus untrustworthy AI behavior, ensuring they are quantifiable in a production environment.

• Lead the establishment of AI observability standards: Set up requirements for telemetry, tracing, logging, and alerting for AI systems and agentic workflows.

• Oversee control validation for agentic systems: Confirm that guardrails, policy checks, access limits, and execution constraints are operating as intended.

• Manage AI security event analysis: Identify, investigate, and document any suspicious, unsafe, or non-compliant AI behaviors while coordinating the response.

• Provide implementation support for governance frameworks: Convert governance principles into technical and operational requirements that product and platform teams can utilize.

• Develop AI trust metrics and reporting: Establish KPIs, KRIs, and dashboards that inform leadership about whether AI systems operate within established trust and security parameters.

• Drive continuous enhancement of AI controls: Utilize incidents, testing, behavioral insights, and stakeholder feedback to improve control design and minimize residual risk over time.

⛳️ Requirements

• A minimum of 5 years of experience in one or more of the following areas: security engineering, detection engineering, observability engineering, site reliability engineering, application security, ML platform engineering, or the implementation of AI governance.

• Proven experience in designing monitoring, logging, telemetry, or detection strategies for distributed systems, cloud services, or data-heavy applications.

• Familiarity with AI/ML system architecture, including large language models, retrieval-augmented generation, inference pipelines, model APIs, and agentic workflows.

• Demonstrated ability to translate governance, risk, or policy requirements into operational controls and quantifiable technical specifications.

• Strong grasp of security concepts such as identity and access management, least privilege, data protection, abuse prevention, auditability, and incident response.

• Experience in investigating system behavior, identifying anomalies, and collaborating across teams to drive remediation efforts.

• Possess industry certifications (or equivalent experience): CISSP, CCSP, GIAC Machine Learning Engineer (GMLE).

• Excellent written communication skills, with the ability to produce standards, control definitions, runbooks, and summaries for leadership audiences.

🏝️ Benefits

• Flexible work hours

• Flexible vacation

• Generous 401K match

• Parental leave

• Team events

• Wellness budget

• Learning reimbursement