The Principal AI Security Engineer acts as an enterprise subject‑matter expert focused on securing AI platforms and the surrounding ecosystem, including agents, integrations, APIs, data sources, and supporting infrastructure. This role identifies AI-specific threats and converts governance and risk expectations into scalable technical safeguards and reusable security patterns across the organization.
Role Focus
- Serve as the enterprise security expert for AI platforms, AI agents, integrations, APIs, and emerging AI use cases.
- Assess AI-related risks, including prompt injection, data exposure, insecure tool invocation, excessive agency, and adversarial inputs.
Key Responsibilities
- Design, implement, and validate security controls for AI platforms, including data protection, access controls, monitoring, guardrails, and approved data-use patterns.
- Perform security architecture reviews, threat modeling, control assessments, and risk‑based evaluations for AI solutions and third‑party services.
- Translate policies, governance requirements, and control frameworks into practical technical requirements, implementation plans, and operational processes.
- Develop monitoring, logging, detection, and investigation capabilities for AI activity and integrate relevant telemetry into security operations.
- Partner with Security Operations and incident response teams to strengthen AI‑related detection, investigation, and response processes.
- Collaborate across technical and governance teams to incorporate security requirements into AI platforms, services, and workflows.
- Create reusable security patterns, implementation guidance, metrics, and evidence to support engineering, governance, risk, and audit activities.
- Monitor changes in AI technologies, threats, and industry guidance, evolving the organization’s security approach accordingly.
Required Qualifications
- 10+ years of experience in security engineering, cloud security, data security, application security, detection engineering, or a related technical security discipline.
- Experience implementing, operating, or validating security controls such as data protection, DLP, SIEM, cloud security, API security, endpoint security, or application security.
- Experience conducting security assessments, architecture reviews, threat modeling, or other risk-based security evaluations.
- Experience translating security risks and governance requirements into practical technical safeguards and implementation plans.
- Strong understanding of data protection, including sensitive data discovery, classification, encryption, privacy, and secure data handling.
- Strong analytical, communication, and collaboration skills to align technical and nontechnical stakeholders on practical solutions.
- Bachelor’s degree.
Preferred Qualifications
- Experience securing AI platforms, AI agents, machine learning systems, or other emerging technologies.
- Knowledge of AI-specific threats, including prompt injection, model misuse, sensitive data exposure, adversarial inputs, and insecure tool invocation.
- Familiarity with AI architectures and services such as APIs, Model Context Protocol services, retrieval-augmented generation, guardrails, and human-in-the-loop controls.
- Experience automating security processes using scripting, APIs, infrastructure as code, or similar approaches.
- Familiarity with NIST AI RMF, NIST Cybersecurity Framework, ISO/IEC 27001, ISO/IEC 42001, or OWASP guidance for AI applications.
- Experience developing reusable security patterns that support emerging technology adoption while managing risk.
Relevant Technologies and Guidance
- Prompt injection
- DLP
- SIEM
- API security
- Endpoint security
- Model Context Protocol services
- Retrieval-augmented generation
- Guardrails
- Human-in-the-loop controls
- NIST AI RMF
- NIST Cybersecurity Framework
- ISO/IEC 27001
- ISO/IEC 42001
- OWASP
Location and Work Schedule
- Natick, MA (hybrid)
- Hybrid schedule: 3 days at the Natick, MA Headquarters and 2 days work from home
Compensation
USD 231,300 per yearly.