VP, Data & AI Architecture

Job Description Summary

Note: This position follows our hybrid-friendly schedule, so you get the best of both worlds – flexibility and collaboration. In office days are 3 days per week (including a Monday or Friday), in our St Petersburg, FL Corporate Office.

This role is not eligible for Work Visa sponsorship, either currently or in the future.

Job Description

This senior technology leader will own the architecture of how the firm governs AI and turns data into insight at scale: the governed path every AI use case takes to production, the inventory and evidence that AI Governance and Model Risk Management rely on, and the data products and shared metrics that let the same trusted answer reach advisors, clients and the business. The role is accountable for speeding up safe AI adoption while meeting the model-risk, privacy and regulatory expectations of a financial services firm.

The role is built for an AI-forward practitioner. The leader in this seat uses AI coding agents such as Claude Code every day in their own work: data discovery, lineage mapping, evaluation harnesses and architecture documentation. They know from practice where generative AI and agents fail, and they build governance into the platform as defaults and automated checks, so teams move faster because the controls come with the path.

This is an individual-contributor role with no direct reports. It partners closely with the data, analytics and AI platform teams, who keep ownership of build and run, and with AI Governance, Model Risk Management, Compliance and Privacy, who keep ownership of policy and approval. It demands strong executive presence, and the credibility to hold a deep technical conversation with engineers and a risk conversation with Compliance in the same day.

Essential Duties and Responsibilities

• Define and maintain the enterprise data and AI target architecture and roadmap: data platforms, data products, streaming data, the shared metrics layer, and machine learning and generative AI platforms.

• Architect AI governance into the platform: one governed path for every AI use case, through the firm's AI gateway, use-case intake, prompt and model registry, evaluation and monitoring. Built in as defaults and automated checks, not added by review at the end.

• Own the AI and model inventory architecture: every AI feature, model and agent is discoverable, tiered by risk, and linked to its data, owners, approvals and validation evidence.

• Set standards for testing and monitoring AI in production: evaluation sets, regression gates on every change, drift monitoring, cost budgets, and tested non-AI fallbacks for advisor- and client-facing features.

• Architect agentic AI safely: agent identity and least-privilege access, scoped tool and data permissions, and complete audit trails.

• Define the data product and ownership model: every critical data set has one owning domain, a data contract, quality targets and lineage, so teams reuse trusted data instead of copying it.

• Architect insight delivery at scale: one definition of each key metric, served consistently to dashboards, advisor tools, APIs and AI assistants, so the same question gets the same answer everywhere.

• Architect retrieval for AI: enterprise search and retrieval-augmented generation over governed content, with entitlements enforced at retrieval and sources cited.

• Embed privacy by design, with Privacy and Information Security: classification, minimization, retention and masking, with client data kept out of non-production systems and model training unless approved.

• Use AI coding agents hands-on to speed up data and AI architecture work, and set the pattern for using them safely. Run architecture review for major data and AI decisions, with recorded decisions and exceptions tracked to closure.

• Measure results: AI use cases in production with complete governance evidence, reuse of certified data products, and time to trusted insight. Collaborate with senior executives on strategy, investment cases and communications.

• Keep a strong external view of data and AI platforms, model providers, AI governance standards and AI regulation in financial services.

What We're Looking For

• A recognized subject-matter expert in data and AI architecture, with 15+ years of hands-on depth across data platforms, analytics, data governance and machine learning, including generative AI in production.

• Proven where the stakes are highest. Experience at a large technology company or a major regulated financial services firm putting AI into production under model-risk, privacy and regulatory oversight. Has run an AI governance framework in practice, not only written the policy.

• AI-forward by habit, not by title. Uses Claude Code or similar agentic tools daily, and can show how AI changed the speed or quality of their work.

• Insights at scale. Has delivered data products or a shared metrics layer adopted across many business lines. Writes SQL and Python, and can defend a data or model decision line by line with engineers, Risk and Compliance.

Certifications:

• Cloud data or machine learning professional-level certification, CDMP, or IAPP AIGP preferred, not required.

Education

Bachelor’s - Completed: Computer and Information Science, High School (HS) - Completed (Required)

Work Experience

General Experience - More than 15 years, Manager Experience - 10 to 15 years

Certifications

Travel

Less than 25%

Workstyle

Hybrid

The total compensation for this position includes base salary or wages, and may include components such as additional compensation (cash or equity), discretionary bonuses, or commissions. This position is eligible for a benefits package that may include medical, dental, and vision; life insurance; critical illness insurance and accident insurance; disability benefits; retirement savings; paid time off (including vacation, holidays, and sick leave); and parental leave.  Eligibility for benefits and specific offerings may vary based on position and employment status. To view more details of the benefits offered, visit Myrjbenefits.com.

 

 

At Raymond James our associates use five guiding behaviors (Develop, Collaborate, Decide, Deliver, Improve) to deliver on the firm's core values of client-first, integrity, independence and a conservative, long-term view. 

We expect our associates at all levels to:
•  Grow professionally and inspire others to do the same
•  Work with and through others to achieve desired outcomes
•  Make prompt, pragmatic choices and act with the client in mind
•  Take ownership and hold themselves and others accountable for delivering results that matter
•  Contribute to the continuous evolution of the firm

At Raymond James – as part of our people-first culture, we honor, value, and respect the uniqueness, experiences, and backgrounds of all of our Associates.  When associates bring their best authentic selves, our organization, clients, and communities thrive. The Company is an equal opportunity employer and makes all employment decisions on the basis of merit and business needs.