Head of Investment AI Strategy

Teacher Retirement System of Texas•Austin, TX

3d•Onsite

About The Position

The Head of Investment AI Strategy is the Investment Management Division’s senior business leader for artificial intelligence. The role leads a small team that works across the division to identify, prioritize, and advance high-value AI opportunities and use cases. The incumbent partners with business, technology, data, security, legal, compliance, and risk functions to advance enterprise AI strategy and governance priorities, translate investment-domain needs into actionable business cases, support adoption and sustainability of AI solutions, and build AI literacy across the division. The position works proactively with internal stakeholders—including Investment Management Division leadership, the Executive Team, the Board, and operational teams—as well as external peers and technology vendors. It advances responsible AI use across the division to help staff make better decisions, increase productivity, and improve business outcomes. The role also represents the division in enterprise AI governance, develops the division’s AI use-case portfolio, and leads delivery through a fusion-team model in which business sets priorities and IT, Data, and Information Security enable scale.

Requirements

Bachelor’s degree from an accredited college or university in Computer Science, Engineering, Data Science, Information Systems, Business Analytics, Mathematics, Statistics, Economics, Finance, or a closely related field; alternatively, a high school diploma or equivalent and additional full-time experience working with artificial intelligence, machine learning, technology strategy, or related experience may be substituted on an equivalent year-for-year basis.
Seven to eight years of full-time, directly related, progressively responsible experience working with artificial intelligence, machine learning, data and analytics, digital transformation, technology strategy, product management, investment management, investment operations, or related work, including demonstrated responsibility for enterprise-scale initiatives and measurable business outcomes.
Three to four years of experience leading multidisciplinary teams, programs, products, or the work of others, including leadership across matrixed business and technology functions.
Three to four years of experience leading or supervising the work of others.
Experience requirements may be concurrent.
A master’s or doctoral degree in a closely related field may be substituted for experience on an equivalent year-for-year basis.
Knowledge of AI technologies, advanced analytics, and their practical business applications.
Knowledge of AI strategy, tool selection, deployment, and lifecycle management in large, matrixed organizations.
Knowledge of data, engineering, product, and technology involved in delivering scalable AI solutions.
Knowledge of investment management concepts and workflows, including research, portfolio management, risk, trading, private markets, and investment operations.
Knowledge of strategic planning, organizational leadership, and management principles.
Knowledge of responsible AI, information security, governance, compliance, and risk management principles.
Skills in strategic planning, stakeholder engagement, and executive and Board communication.
Skills in partnering with investment and business leaders to identify and advance AI solutions that support organizational objectives.
Skills in translating business needs into clear business cases, requirements, and measurable outcomes.
Skills in developing and executing strategic initiatives in complex, technology-driven environments.
Skills in leading multidisciplinary teams and complex initiatives across business and technology functions.
Skills in evaluating emerging technologies and industry practices and determining their relevance to the business.
Skills in analyzing complex issues, exercising sound judgment, and developing actionable recommendations.
Skills in leading and developing teams while managing multiple priorities and driving results.
Ability to develop and execute strategic initiatives that support business goals.
Ability to deliver AI solutions that improve investment insights, decision quality, productivity, risk management, and operational outcomes.
Ability to translate strategic priorities into operational results and measurable business value.
Ability to evaluate AI technologies and determine appropriate business applications.
Ability to navigate enterprise governance and build consensus across business, technology, risk, and other stakeholders.
Ability to present complex concepts and recommendations clearly to executive leadership, boards, and diverse stakeholders.
Ability to build effective partnerships and influence decision-making across business and technology functions.
Ability to exercise sound judgment and appropriately address technology, information security, and AI-related risks.
Ability to influence, develop, and lead high-performing multidisciplinary teams, including matrixed partners and vendors.
Ability to promote innovation, accountability, and continuous improvement.

Nice To Haves

Bachelor’s degree from an accredited college or university in Computer Science, Engineering, Data Science, or a closely related field.
Ten years of full-time experience leading the evaluation, deployment, governance, and business application of AI technologies and platforms in large, matrixed organizations, including collaboration with data science, engineering, product, investment management, investment operations, and business teams to deliver AI-enabled solutions.
Experience operating within a centralized technology governance model in a regulated or public sector environment, including advancing business technology needs through formal review, risk assessment, and procurement processes.
Experience in investment management, asset management, financial services, public pensions, or another highly regulated and risk-managed environment.
Professional certifications in artificial intelligence, machine learning, data science, AI governance, Responsible AI, cloud-based AI platforms, or related disciplines.

Responsibilities

Identify and evaluate AI capabilities against Investment Management Division business needs and advance recommendations through technical, security, and enterprise review processes.
Serve as business product owner for approved Investment Management Division AI initiatives.
Partner with risk, compliance, data, and security teams to embed responsible AI requirements into use cases and delivery plans.
Translate enterprise and executive KPIs into initiative-level success measures and report outcomes to division and enterprise leadership.
Drive adoption and operationalization of approved AI tools and platforms, partnering with investment teams to address critical needs and reduce bottlenecks.
Identify and escalate AI-related risks through enterprise risk and governance processes and communicate status transparently to senior leadership.
Represent the Investment Management Division in AI-related governance and contribute investment-domain expertise to enterprise AI strategy, roadmap development, and policy.
Advance division priorities through established governance processes and help resolve technical and security questions early.
Advise on and adhere to enterprise technical standards, responsible AI practices, and TRS AI policies.
Manage stakeholder expectations regarding approval timelines, resource capacity, and the approved technology catalog.
Develop a network with peer public pension funds, sovereign wealth funds, and external managers, and share applicable insights with the enterprise AI community.
Collaborate with division leadership on governance, strategic planning, and organizational performance.
Provide recommendations, reports, analysis, and presentations to support executive and Board decision-making.
Develop and drive the division’s AI use-case portfolio and business priorities and ensure they are reflected in the enterprise AI roadmap.
Monitor emerging AI technologies relevant to investment management and partner across the organization to evaluate capabilities through appropriate pilots and testing environments.
Collaborate with division leadership, investment teams, division AI Champions, and enterprise AI Champions to advance adoption, build organizational capability, and support strategic objectives.
Lead and develop a small AI team by setting priorities, allocating work, coaching performance, and coordinating delivery through the fusion-team model.
Partner with enterprise partners to expand AI training, tools, and responsible AI guidance across the division and develop reusable investment-specific use-case examples.
Perform related work as assigned.