Principal--Data, Analytics & AI Architect

Fannie Mae•Reston, VA

1d•$200,000 - $269,000•Onsite

About The Position

As Principal, Data, Analytics & AI Architect, you will provide strategic architecture leadership for Fannie Mae’s enterprise data and AI platforms. You will define standards and roadmaps, guide key technology decisions, and ensure solutions are secure, scalable, resilient, and aligned with risk, and regulatory priorities. You will partner with business and technology leaders to guide investment decisions, evaluate architectural trade-offs, and ensure platform capabilities deliver measurable business outcomes.

Requirements

8 years of progressively responsible experience across application development, data science and analytics, enterprise architecture, and technology strategy.
Deep expertise in cloud, data, and AI/ML concepts, supported by hands-on experience designing and architecting data and AI capabilities on cloud.
Proven expertise in leading large-scale, cross-functional enterprise-wide initiatives involving data and AI/ML platforms with measurable business outcomes.
Strong understanding of data governance, model risk, responsible AI, and regulatory expectations in financial services or similarly regulated environments.
Proven experience leading complex, cross-functional initiatives while aligning multiple stakeholders and balancing competing priorities.
Demonstrated success delivering complex, high‑stakes enterprise solutions in regulated or risk‑sensitive environments
Experience supporting executive leadership, governance committees, and strategic decision-making processes.
Strong written and verbal communication skills with the ability to communicate complex information to executive audiences.
Shows curiosity and adaptability in learning and responsibly applying new technologies, including artificial intelligence, to reimagine how we work.

Nice To Haves

Proven experience architecting and providing enterprise-level oversight for AI, machine learning, generative AI, data, and analytics platforms.
Demonstrated ability to define enterprise architecture strategies, reference architectures, technology standards, reusable patterns, and multi-year transformation roadmaps aligned with business objectives and measurable outcomes.
Strong expertise in AWS cloud and Databricks, including the architecture of scalable, secure, resilient, and mission-critical data and AI platforms.
Broad knowledge across application, integration, data, infrastructure, security, and business architecture domains, with the ability to evaluate architectural trade-offs, technical debt, platform maturity, and build-versus-buy decisions.
Knowledge of AI governance frameworks, responsible AI principles, model risk management, and industry-leading practices.
Experience establishing architecture governance, decision rights, and accountability across centralized platform teams, business units, and product teams.
Experience in financial services or similarly regulated environments, with a strong understanding of risk management, compliance, and regulatory requirements.
Strong executive communication and stakeholder-management skills, including experience supporting governance reporting, organizational change, and senior-level decision-making.

Responsibilities

Provide Data, Analytics & AI architecture leadership and oversight for mission-critical data, analytics, AI/ML, and generative AI platforms.
Define and maintain Data, Analytics & AI architecture strategies, reference architectures, technology standards, reusable patterns, and multi-year transformation roadmaps.
Participate/ Lead architecture reviews and assess solutions for scalability, security, resilience, interoperability, cost efficiency, technical debt, and build-versus-buy considerations.
Lead/ Establish architecture and AI governance in partnership with cybersecurity, risk, compliance, legal, data governance, and platform teams.
Serve as an advisory to senior leadership on technology investments, platform modernization, architectural risks, and alignment with business and regulatory objectives.