Cloud Artificial Intelligence Security Lead

Cloud Artificial Intelligence Security Lead

This role at Arbitration Forums is as unique as it is rewarding because of the AF IPAAL Values (Integrity, Passion, Accountability, Achievement, Leadership) and TRI Model (Trust, Respect, Inclusion).

The Artificial Intelligence Security Lead is a dynamic, empathetic, and action-oriented individual who plays a crucial role in ensuring that our AI products and solutions uphold the highest standards of security and compliance.

This role is accountable for the definition and implementation of security design patterns for cloud-based security services, ensuring that the AI cloud security framework is optimized to support the life cycle of AF's AI-powered solutions.

The Artificial Intelligence Security Engineer creates execution strategies that focus on embedding security controls into AI models and solution designs and builds practices to allow proactive rather than reactive focus.

• Adheres to AF Policy and Procedures and the AF IPAAL Values and TRI Model

• Acts as a role model within and outside AF.

• Performs duties as workload necessitates.

• Maintains a positive and respectful attitude.

• Communicates regularly with the departmental leader about department issues.

• Demonstrates flexible and efficient time management and ability to prioritize workload.

• Consistently reports to work on time, prepared to perform duties of the position.

• Meets Department productivity standards.

• Collaborate with the Data Governance Lead and Compliance SMEs to define and implement the operational procedures for data cataloging and lineage harvesting and plotting, with a focus of ensuring that the data utilized in exploration and throughout the model development lifecycle is secured and compliant with AF's policies.

• Develop and implement policy driven data protection best practices to ensure AI cloud solutions are protected from data loss.

• Collaborate closely with data scientists, GenAI specialists and developers, and MLOps engineers, to identify potential security vulnerabilities, implement best practices, and ensure compliance with regulatory standards including NIST, SOC 2, and others.

• Lead security assessments, coordinate penetration testing, and ensure vulnerability management for AI systems to proactively mitigate risks.

• Support Data Governance by acting as the security expert throughout the designing, developing, and deploying of secure AI and machine learning applications, with a focus on safeguarding personally identifiable information (PII).

• Stay ahead of emerging cybersecurity threats, privacy regulations, and compliance requirements to ensure that our AI solutions continuously meet and exceed market standards.

• Document security protocols, conduct training sessions, and promote security awareness within the team and organization.

• Engage with stakeholders across multiple disciplines to refine security policies and procedures specific to AI and ML products.

• Design, implement, and execute test approaches to GenAI to identify security flaws, particularly those impacting confidentiality, integrity, or availability of information.

• Partner with Quality Assurance department on the creation, implementation, and execution of test plans and strategies for evaluating the compliance of AI systems, including defining test objectives, selecting suitable testing methods, and identifying test scenarios.

• Support the documentation of test methods, results, and suggestions in clear and brief reports to stakeholders.

• Participate in the automation of security test cases and optimize the coverage and performance of automated test scripts.

• Perform security assessments including creating updating and maintaining threat models and security integration of Gen AI platforms.

• Implement/configure security controls on AI technologies.

• Discuss AI/ML concepts proficiently with data science and ML teams to identify and develop solutions for security issues.

• Support the identification and documentation of defects, irregularities or inconsistencies in AI systems working closely with quality assurance, data scientists, GenAI engineers and AI developers to rectify and resolve them.

•…