Job Overview: The AI Governance organization is seeking a Vice President, AI Governance to own the firm's enterprise AI governance strategy and provide authoritative oversight and credible challenge across the AI lifecycle. This leader will establish the governance framework, risk standards, decision rights, and oversight expectations that enable responsible AI adoption while protecting the firm, its clients, and its regulatory standing.
This is not a policy administration or committee coordination role. The Vice President must understand how AI solutions are designed, trained or configured, integrated, deployed, and monitored; independently assess whether risks and controls are understood; challenge business and technical teams beyond vendor claims and management assertions; and drive clear decisions on approval, conditions, remediation, escalation, or risk acceptance. The role will advise senior executives and governance committees and represent the program in regulatory, audit, and other independent reviews.
Roles & Responsibilities: - Own and evolve the enterprise AI Governance Framework, including policies, standards, risk taxonomy, risk-tiering methodology, approval authorities, decision rights, lifecycle requirements, monitoring expectations, and escalation protocols.
- Set the strategic direction and target operating model for AI governance, translating regulatory developments and emerging AI risks into practical, examination-defensible requirements.
- Provide independent review and credible challenge of AI and machine learning use cases, including generative AI, large language models, AI agents, predictive models, embedded vendor capabilities, and other AI-enabled solutions.
- Evaluate AI solutions at the architecture, model, data, integration, security, third-party, control, and operating-process levels to identify material risks, unsupported assumptions, control weaknesses, and residual exposure.
- Challenge business and technical owners on use-case design, data suitability and lineage, model behavior, testing, validation, human oversight, guardrails, access, monitoring, incident response, change management, and decommissioning.
- Chair or lead enterprise AI governance forums and drive risk-based decisions, ensuring material conditions, exceptions, risk acceptances, and unresolved matters are clearly documented, assigned, monitored, and escalated.
- Serve as the senior AI governance advisor to executive leadership, providing concise recommendations on whether and under what conditions AI capabilities should proceed.
- Establish clear accountability across Business, Technology, Information Security, Data Governance, Privacy, Legal, Compliance, Model Risk, Third-Party Risk, Enterprise Risk Management, and Internal Audit.
- Define meaningful key risk indicators, performance measures, portfolio insights, and executive reporting that show AI exposure, control effectiveness, exceptions, issues, emerging risks, and program maturity.
- Oversee regulatory examinations, Internal Audit reviews, independent assessments, and other inquiries involving AI governance, and ensure identified gaps are translated into sustainable remediation.
- Build and lead a high-performing AI governance team with the judgment, technical fluency, and discipline needed to operate a credible second-line oversight program.
- Promote responsible innovation by providing timely, practical governance that distinguishes manageable risk from unacceptable exposure rather than defaulting to either approval or prohibition.
What are we looking for?We're looking for strong collaborators who deliver exceptional client experiences and thrive in fast-paced, team-oriented environments. Our ideal candidates
pursue greatness,
act with integrity, and are
driven to help our clients succeed. We value those who embrace creativity, continuous improvement, and contribute to a culture where we
win together and
create and share joy in our work.
Requirements: - Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, Risk Management, Finance, Law, Public Policy, or a related discipline. Advanced degree preferred.
- 10+ years of progressive experience in technology risk, model risk, artificial intelligence governance, cybersecurity, data risk, compliance, audit, or a related control discipline within financial services or another highly regulated industry.
- 5+ years of direct experience reviewing, governing, validating, auditing, implementing, or overseeing artificial intelligence, machine learning, advanced analytics, or model-based solutions.
- Demonstrated experience challenging AI solutions at the architecture, model, data, and control levels, with the ability to explain how the solution functions, where risk originates, and whether proposed controls are sufficient.
- Proven experience establishing or materially enhancing an enterprise governance, risk, or control framework, not solely advising on or documenting one.
Core Competencies - Advanced working knowledge of AI and machine learning concepts, including generative AI, large language models, retrieval-augmented generation, AI agents, training and inference, prompt-based systems, model evaluation, monitoring, and third-party AI services.
- Deep understanding of AI risk domains, including model performance, explainability, bias and fairness, data quality and lineage, privacy, cybersecurity, intellectual property, recordkeeping, consumer protection, third-party dependency, resilience, and operational integration.
- Credible challenge: asks precise questions, tests assumptions, identifies what is missing, and distinguishes evidence from assertion.
- Risk judgment: converts complex and sometimes conflicting technical, legal, regulatory, and business considerations into a clear recommendation and defensible decision.
- Executive communication: explains technical risk without jargon, frames tradeoffs, and produces concise materials that support action rather than discussion alone.
- Leadership and influence: drives accountability across a matrixed organization, resolves ambiguity in roles and decision rights, and maintains independence while building productive partnerships.
- Execution discipline: sets standards, closes gaps, escalates when necessary, and measures whether governance is changing outcomes rather than producing activity.
- Demonstrated ability to make and defend difficult risk recommendations when facts are incomplete, stakeholders disagree, or business pressure is significant.
- Experience advising executives and governance committees and representing a program in regulatory examinations, Internal Audit reviews, or comparable independent challenge.
- Prior people leadership experience, including building capability, setting clear standards, and holding teams and stakeholders accountable for execution.
Preferences - Experience leading AI governance, responsible AI, AI assurance, model risk, AI audit, or emerging technology risk within a broker-dealer, wealth management firm, bank, insurer, or other regulated financial institution.
- Hands-on experience with AI development, model validation, technical architecture, technology risk assessment, control testing, or AI assurance.
- Knowledge of the NIST AI Risk Management Framework, ISO/IEC 42001, ISO/IEC 23894, model risk management principles, and emerging U.S. and global AI regulatory expectations.
- Relevant professional certification such as AIGP, CRISC, CISSP, CISM, CISA, FRM, or comparable credential.
Pay Range: $137,093.00 - $228,454.00
Actual base salary varies based on factors, including but not limited to, relevant skill, prior experience, education, base salary of internal peers, demonstrated performance, and geographic location. Additionally, LPL Total Rewards package is highly competitive, designed to support your success at work, at home, and at play - such as 401K matching, health benefits, employee stock options, paid time off, volunteer time off, and more. Your recruiter will be happy to discuss all that LPL has to offer!
