AI Risk Architect

Role Description

The AI Risk Architect will be responsible for identifying, assessing, and mitigating risks associated with artificial intelligence systems deployed across the organization and for clients. This strategic role combines technical expertise in AI systems with a deep understanding of risk management frameworks, regulatory compliance, and ethical considerations. The AI Risk Architect will work cross-functionally to develop governance structures that enable innovation while ensuring responsible AI deployment.

Key Responsibilities

• Develop comprehensive AI risk assessment frameworks tailored to different AI systems and use cases
• Lead risk identification workshops with technical and business stakeholders
• Design and implement AI governance structures, policies, and procedures
• Evaluate AI systems for potential biases, security vulnerabilities, and compliance issues
• Create mitigation strategies for identified AI risks while balancing innovation needs
• Collaborate with data science, legal, compliance, and business teams on responsible AI initiatives
• Stay current with evolving AI regulations, standards, and best practices
• Advise senior leadership on emerging AI risks and opportunities
• Develop client-facing methodologies for AI risk assessment and management
• Contribute to thought leadership in the AI risk management space

Job Profile

Qualifications

• Master's degree or higher in computer science, data science, risk management, or related field
• 7+ years of experience in technology risk management, with at least 3 years focused on AI/ML systems
• Strong understanding of machine learning algorithms, data analysis, and AI system architecture
• Experience with AI auditing tools and methodologies
• Knowledge of relevant regulatory frameworks (e.g., EU AI Act, NIST AI RMF)
• Excellent communication skills with ability to translate technical concepts for non-technical audiences
• Proven ability to develop and implement governance frameworks and policies
• Experience working with cross-functional teams and C-suite executives

Technical Skills

• Proficiency in at least one programming language commonly used in AI/ML (Python, R)
• Understanding of model documentation techniques and model cards
• Familiarity with common AI fairness and explainability tools
• Knowledge of data privacy techniques (e.g., differential privacy, federated learning)
• Experience with risk assessment methodologies and documentation

Preferred Qualifications

• Professional certifications in risk management, data ethics, or AI governance
• Previous consulting experience in a Big Four or similar professional services firm
• Published work or presentations on AI ethics, risk, or governance topics
• Experience in highly regulated industries (finance, healthcare, etc.)
• Knowledge of auditing procedures and documentation standards