Sr. AI Security Engineer

Develop and maintain enterprise AI security standards, control requirements, and risk-based review processes.

Assess AI applications, models, agents, APIs, integrations, vendors, and data flows before and after deployment.

Define security requirements for AI systems across design, development, testing, deployment, operation, and retirement.

Evaluate identity, access, identity governance, data protection, privacy, logging, monitoring, retention, and human-oversight controls.

Test AI systems and agent workflows for prompt injection, indirect injection, jailbreaks, data leakage, excessive agency, unsafe tool use, insecure integrations, and configuration drift.

Conduct threat modeling, architecture reviews, security assessments, and control validation for AI-enabled solutions.

Establish processes for AI security findings, incident response, exception management, remediation, and executive reporting.

Review AI vendors, models, third parties, subprocessors, data handling practices, and material platform or configuration changes.

Configure, tune, validate, operate, and extend existing AI-security, AI-governance, application-security, data-security, and monitoring tools.

Support the evaluation and integration of additional capabilities where existing controls require enhancement.

Create practical security patterns, reference architectures, playbooks, standards, and guidance for engineering and product teams.

Monitor emerging AI threats, vulnerabilities, standards, regulations, and industry practices and translate them into actionable improvements.

Partner with development and platform teams to integrate security controls into AI development and deployment workflows.

Communicate technical risks, business impact, and recommended actions to both technical and non-technical stakeholders.

Promote responsible AI adoption through measurable controls, clear accountability, and continuous improvement.

Bachelor’s degree in cybersecurity, computer science, information systems, engineering, or a related field, or equivalent professional experience.

Minimum five years of proven experience in an established security architecture, security engineering, architecture, or engineering role.

Working experience handling AI security in a production environment, including the assessment, governance, monitoring, or protection of AI applications, models, agents, or integrations.

Strong understanding of cybersecurity principles, including identity governance, least privilege, data protection, risk assessment, incident response, security architecture, and security governance.

Familiarity with OWASP LLM and AI risks, including prompt injection, indirect injection, jailbreaks, sensitive information disclosure, excessive agency, insecure output handling, and agent or tool-use security.

Practical understanding of generative AI architectures, large language models, retrieval-augmented generation, AI agents, APIs, and model or application lifecycle risks.

Ability to explain how risks such as indirect prompt injection or excessive agency would surface in a real agent workflow and how those risks could be detected, validated, and mitigated.

evaluating security controls, technology vendors, data handling practices, privacy considerations, and third-party risk.

Ability to develop clear standards and communicate complex technical risks to engineers, product teams, business leaders, and executives.

Strong analytical, written, verbal, collaboration, and problem-solving skills.

Sound judgment, personal integrity, curiosity, and a demonstrated commitment to protecting confidential information.

Experience with AI-security, application-security, cloud-security, data-security, DevSecOps, or security-monitoring tools.

performing AI red teaming, adversarial testing, penetration testing, threat modeling, or control validation.

Familiarity with the NIST AI Risk Management Framework or comparable AI-governance frameworks.

integrating security controls into software development, cloud engineering, or platform operations.

Familiarity with data classification, DLP, audit logging, security information and event management, and privacy-by-design practices.

Relevant certifications such as CISSP, Security+, or a portfolio demonstrating comparable practical experience.

McCarthy is proud to be an equal opportunity employer, including disability and protected veteran status.

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