ABOUT THE ROLEThe
Associate Manager, AI Security Engineer helps enable the rapid, responsible, and secure adoption of artificial intelligence across the business. This hands-on engineering and development opportunity is intended for an application, data, cloud, AI/ML, infrastructure, or cybersecurity professional who wants to grow into the emerging field of AI security.
The successful candidate is not expected to begin as an expert in every area of AI or cybersecurity; through hands-on experience, collaboration, mentoring, and targeted development, the engineer will build expertise in AI security architecture, threat modeling, adversarial testing, governance controls, secure AI engineering, and AI-enabled cybersecurity capabilities.
The engineer will assess risks, identify vulnerabilities, help design and implement security controls, and work with business and technology teams to protect information and systems while preserving the functionality, usability, and business value of AI solutions.
KEY RESPONSIBILITIES- Translate AI security policies, standards, and architecture requirements into practical engineering controls, reusable implementation patterns, test criteria, and evidence-producing processes.
- Design and build AI-enabled cybersecurity solutions, workflows, and automation that improve detection, investigation, response, vulnerability reduction, and control validation.
- Design, implement, and validate safeguards against AI-specific and traditional security threats, including prompt injection, data exposure, unsafe tool use, excessive agency, model abuse, identity misuse, and supply-chain risk.
- Support AI development teams with secure build and implementation practices, including approved library and dependency management, secure MCP and tool-integration patterns, controlled data-access designs, identity and permission configuration, secrets handling, and approved security patterns.
- Define and execute security validation methods for AI solutions, including threat modeling, adversarial testing, control testing, secure configuration review, and readiness checks before production deployment.
- Establish logging, monitoring, alerting, and response capabilities so AI-related activity, risks, and incidents can be detected, investigated, contained, and improved over time.
- Communicate AI security risks, options, trade-offs, and recommendations in clear business terms to support responsible AI adoption; stay current on AI technologies, threats, regulations, and standards and apply relevant developments to security controls and engineering practices.
REQUIRED EXPERIENCE YOU'LL BRING- Bachelor's degree in cybersecurity, computer science, engineering, information systems, data science, artificial intelligence, or a related discipline, or equivalent relevant education and practical experience.
- 5+ years of relevant hands-on engineering experience in one or more areas such as application or software development, data engineering, cloud engineering, AI/ML, platform engineering, infrastructure, identity and access management, DevOps, or cybersecurity.
- 5+ years of experience designing, building, supporting, testing, or securing enterprise technology solutions, applications, cloud services, data platforms, infrastructure, or security technologies.
PREFERRED EXPERIENCES AND SKILLS- Foundational understanding of cybersecurity principles such as identity and access management, data protection, secure application design, vulnerability management, cloud security, logging and monitoring, or risk management.
- Familiarity with cloud services, APIs, application development, data platforms, scripting, infrastructure as code, CI/CD pipelines, AI platforms, or security tools.
- Exposure to generative AI, agentic AI, machine learning, natural-language processing, data science, AI application development, or machine-learning operations.
- Experience with one or more major AI or cloud ecosystems, such as Microsoft Azure AI and Copilot, OpenAI, AWS Bedrock, Google Vertex AI, or comparable enterprise services.
- Familiarity with security risks affecting AI-enabled solutions, including prompt injection, insecure tool use, excessive agency, sensitive-data disclosure, unsafe output handling, identity misuse, and third-party or supply-chain risk.
- Strong communication, collaboration, analytical, and problem-solving skills, including the ability to explain technical risks, trade-offs, and recommendations to technical and non-technical stakeholders.
- Relevant professional certifications in cybersecurity, cloud, architecture, software development, data, or AI are valued but are not required for consideration.
JOB REQUIREMENTS- Office work environment: Remote work available once a week for eligible employees.
- This role is not eligible for relocation.
