AI Governance Architecture for High-Stakes Decisions

I help banks, insurers, and public-sector institutions design AI systems with assurance built in: verifiable, governable, and accountable from the first requirement.

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About

I'm Federico J. Quijada, an AI governance architect and executive educator based in Chicago.

For more than twenty years I led technology programs at AIG, Blue Cross Blue Shield, Wells Fargo, and United Airlines, including a $6 million AI/ML program at United. That work taught me that what holds enterprise AI back is rarely capability. It is architecture.

My doctoral research at Purdue University focuses on memory-centric AI architecture for executive decision-making: systems where verification, accountability, and governance are designed in from the start rather than added after deployment. I present this work at venues including MIT and Stanford, and teach AI leadership in executive programs at MIT, Cambridge, and Cornell.

My legal training (JD, Villanova) means I treat governance and compliance as design requirements, not afterthoughts.

Education

2023 to present

Doctor of Technology (AI), Candidate,

Purdue University

My doctoral work is where the other four degrees converge. At Purdue's ROCkETEd Lab I design and test a memory-centric AI architecture for decision-making in regulated environments, one in which governance, verification, and accountability are part of the system's structure rather than policies added after deployment. The questions I learned to ask as a lawyer, a technology leader, and a student of AI's ethical and security consequences become engineering requirements here.

2025

Master of Liberal Arts,

University of Chicago

The Master of Liberal Arts let me study AI as a scientific, philosophical, and ethical problem at once. My thesis examined AI and machine learning at the network edge: how models running on IoT devices change the security picture, and who answers for a decision when it is made far from the data center. That work shifted my focus from what AI can do to where it runs, how it fails, and how an institution would know.

2022

Master of Science in Technology Leadership,

Brown University

Brown's program tied leadership to the realities of running technology inside large organizations: strategy, operating models, and the decisions that determine whether a new system is adopted or quietly abandoned. It gave me a structured way to read the gap between a sound technical design and an institution's ability to use it well. Most AI programs that stall, stall in that gap.

Juris Doctor,

Villanova University

Law school trained me to read a system the way a regulator, a court, or opposing counsel would. Studying corporate and business law showed me how institutions take on obligations and how they are held to account when something goes wrong. I still work through that lens: regulatory requirements are design constraints, and a decision that cannot be explained cannot be defended.

Bachelor of Arts,

Saint Anselm College

My liberal arts education at Saint Anselm taught me to reason carefully, write clearly, and take seriously the human questions behind institutional choices. It is why I treat AI as a matter of judgment and responsibility, not only capability, and why I work to explain complex technology in terms leaders can act on.