Job Description:
At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. We do this by driving Responsible Growth and delivering for our clients, teammates, communities and shareholders every day.
Being a Great Place to Work and providing a culture of caring is core to how we drive Responsible Growth. We are intentional about fostering an inclusive workplace where every teammate has the opportunity to succeed, build a career and contribute to our shared success. This includes attracting and developing exceptional talent, recognizing and rewarding performance, and supporting our teammates’ physical, emotional, and financial wellness through affordable, competitive and flexible benefits.
We value the unique perspectives individuals bring from all backgrounds and career paths - whether shaped by military service, community college education, or a wide range of work and life experiences. These journeys foster resilience, leadership and innovation, strengthening our workforce and positively impact the communities we serve.
Bank of America is committed to an in-office culture that supports collaboration, engagement, and career development. Our approach includes clear in-office expectations, while providing an appropriate level of flexibility based on role-specific responsibilities and business needs.
At Bank of America, you can build a successful career with opportunities to learn, grow, and make an impact. Join us!
Job Description:
This job is responsible for the execution of data architectural solutions for complex initiatives that span multiple Lines of Business and control functions. Key responsibilities include facilitating solution driven discussions, working with stakeholders to support adherence to the enterprise data management policy and standards, and supporting architecture design reviews to ensure integration of data architecture principles in technology solutions. Job expectations include educating data management teams on enterprise data architectural principles and data management processes and routines.
The Senior AI Controls Lead is responsible for leading the design, implementation, assessment, and continuous improvement of AI control capabilities across Global Technology (GT). This role partners with technology, risk, compliance, information security, legal, and governance teams to ensure AI solutions are developed, deployed, and operated in a secure, compliant, and responsible manner.
Key responsibilities include establishing AI control requirements, assessing AI solutions and platforms against enterprise standards, identifying control gaps and remediation strategies, and driving adoption of consistent AI governance practices across Global Technology. The ideal candidate combines expertise in artificial intelligence, governance, risk management, technology controls, and regulatory compliance with a deep understanding of emerging AI risks and control requirements in highly regulated environments.
Responsibilities:
- Partners with various technology teams to establish data solutions and architecture for large, complex initiatives that align with the enterprise data architecture strategy and strategic technology and platform decisions
- Develops clear and concise responses to questions from senior management and control partners regarding the enterprise data architecture strategy
- Manages multiple priorities in a matrixed environment with attention to detail and accuracy
- Communicates effectively to influence agreement between partners and escalates items, as needed, to ensure execution activities remain on track
- Ensures all relevant risk, financial, and compliance policies and standards are met
- Manages relationships with business and technology partners and creates an inclusive and healthy working environment to resolve organizational impediments and blockers
- Educates data management teams on enterprise data architectural principles, processes, and routines
AI Controls Strategy, Governance & Oversight
- Lead the development and evolution of GT AI control capabilities and governance practices.
- Define and maintain AI control requirements aligned with enterprise policies, risk management standards, regulatory expectations, and industry frameworks.
- Partner with Risk, Compliance, Information Security, Model Risk Management, Legal, and Engineering teams to ensure consistent implementation of AI controls.
- Support the development and adoption of AI policies, standards, procedures, and governance processes across Global Technology.
- Provide subject matter expertise on AI risks, control design, governance, and emerging regulatory expectations.
- Develop executive-level communications and responses regarding AI governance, AI controls, and enterprise AI risk management.
- Influence enterprise AI strategy through the establishment of scalable governance and control practices.
- Manage multiple priorities in a matrixed environment with a high degree of accuracy, accountability, and attention to detail.
- Build strong partnerships across technology and control functions to remove obstacles and drive execution.
AI Controls Design & Implementation
- Establish and maintain control frameworks and technical guardrails supporting AI and Generative AI solutions.
- Define standardized control patterns for:
- Identity and access management
- Data protection and privacy
- Content filtering and safety controls
- Prompt governance
- AI monitoring and observability
- Auditability and traceability
- Evaluate solutions supporting explainability, transparency, bias detection, red teaming, safeguard monitoring, and operational resilience.
- Drive integration of AI controls into technology delivery, operational processes, and platform onboarding activities.
- Promote consistent implementation of GT AI Control Framework requirements across AI systems and platforms.
AI Controls Assessment & Assurance
- Conduct formal assessments of AI platforms, tools, and solutions to determine control maturity and alignment with enterprise requirements.
- Evaluate third-party AI providers and AI-enabled technologies against security, privacy, operational, governance, and compliance requirements.
- Lead control readiness reviews for Generative AI, Agentic AI, machine learning solutions, AI development frameworks, and AI-enabled technology platforms.
- Identify risks, control gaps, and remediation actions required before implementation.
- Develop repeatable assessment methodologies and evaluation criteria to support control reviews.
- Assess control effectiveness across:
- Data protection
- Access management
- Safeguard controls
- Responsible AI requirements
- Monitoring and observability
- Logging and auditability
- Model transparency and explainability
- Provide recommendations, risk mitigation strategies, and governance guidance based on assessment outcomes.
AI Lifecycle Controls & Risk Management
- Ensure appropriate controls are implemented throughout the AI lifecycle from design through retirement.
- Support governance processes covering:
- AI solution onboarding
- Risk assessments
- Testing and validation
- Change management
- Monitoring and reporting
- Issue management and remediation
- Promote consistent implementation of Responsible AI principles, including transparency, fairness, explainability, accountability, and robustness.
- Establish monitoring and reporting practices for AI risks, control effectiveness, compliance, and operational performance.
- Support regulatory, audit, and risk management activities related to AI systems and controls.
Leadership & Influence
- Serve as a trusted advisor to senior technology and risk leaders on AI governance, controls, and responsible AI practices.
- Influence strategic direction for AI risk management and control capabilities across Global Technology.
- Lead cross-functional initiatives to improve AI control maturity and operational effectiveness.
- Communicate effectively with executive leadership, auditors, regulators, and technology teams.
- Foster collaboration across business, technology, governance, and control organizations.
- Help shape the future direction of enterprise AI governance through alignment to evolving regulatory expectations and industry-leading practices.
Required Qualifications:
- 10+ years of experience in technology risk, information security, technology controls, AI governance, AI engineering, enterprise architecture, or related technology leadership roles.
- Demonstrated experience assessing AI solutions, AI platforms, and AI control capabilities.
- Deep understanding of AI governance, AI risk management, Responsible AI principles, and technology control frameworks.
- Experience developing and implementing controls for AI, machine learning, and Generative AI technologies.
- Strong knowledge of:
- Generative AI and Large Language Models (LLMs)
- Agentic AI and orchestration frameworks
- Retrieval-Augmented Generation (RAG) architectures
- Model monitoring and observability
- Identity and access management
- Data protection and privacy controls
- Information security controls and platform governance
- Experience working within highly regulated environments.
- Strong executive communication, stakeholder management, and influencing skills.
Desired Qualifications:
- Experience in financial services or other highly regulated industries.
- Experience supporting AI governance, model risk management, technology risk, or control organizations.
- Knowledge of industry frameworks and standards including:
- NIST AI Risk Management Framework (AI RMF)
- OWASP Top 10 for LLM Applications
- ISO 42001 AI Management Systems
- Financial services regulatory guidance and emerging AI regulations
- Experience supporting AI governance for Agentic AI, RAG architectures, LLMOps platforms, and AI observability solutions.
- Professional certifications in AI governance, cloud architecture, information security, risk management, or related disciplines.
Core Competencies
- AI Governance & Controls
- AI Risk Management
- Information Security & Technology Controls
- Responsible AI
- Regulatory Compliance
- Risk Assessment & Control Design
- AI Platform Governance
- Executive Communications
- Strategic Leadership
- Cross-Functional Influence
- Technology Governance
- Control Assessment & Assurance
Success Measures
- Consistent adoption of AI controls across Global Technology.
- Increased AI governance and control maturity across AI platforms and solutions.
- Measurable reduction in AI-related risk exposure.
- Improved regulatory, audit, and compliance readiness.
- Successful implementation of GT AI Control Framework requirements.
- Strengthened transparency, traceability, and monitoring of AI systems.
- Strong partnership across Technology, Risk, Compliance, Information Security, Legal, and Governance teams.
- Delivery of scalable, secure, compliant, and responsible AI solutions.
Skills:
- Architecture
- Business Analytics
- Critical Thinking
- Data Management
- Data Visualization
- Consulting
- Data Modeling
- Process Design
- Regulatory Compliance
- Risk Management
- Cloud Solutions
- Collaboration
- Data Governance
- Talent Development
- Technical Strategy Development
Shift:
1st shift (United States of America)
Hours Per Week:
40
