AI Governance Architect

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AI Governance Architect

Role Summary

We are seeking an experienced AI Governance Architect to establish and operationalize enterprise-wide AI governance capabilities within a leading Financial Services organization. This role will be responsible for defining AI governance frameworks, building and managing an enterprise AI Registry, governing AI agents and AI applications, and designing evaluation frameworks to ensure responsible, compliant, and scalable AI adoption.

The ideal candidate will combine expertise in enterprise architecture, AI/Agentic AI governance, cloud platforms, risk management, and Financial Services regulations, with experience working across technologies such as Claude LLM, OpenAI Custom GPTs, AWS, AI Agents, MCP Servers, and enterprise AI applications .

Key Responsibilities

AI Governance Strategy & Framework

• •Define and implement the enterprise AI Governance strategy, operating model, standards, and control frameworks.
• •Establish governance scope covering AI models, AI agents, GenAI applications, MCP servers, AI tools, prompts, datasets, and supporting infrastructure.
• •Create policies, lifecycle controls, approval workflows, and risk management processes for AI assets.
• •Partner with Risk, Compliance, Security, Legal, Data, and Business stakeholders to operationalize AI governance.

AI Registry & Enterprise AI Inventory

• •Define the vision, architecture, and operating model for an enterprise-wide AI Registry .
• •Design and build a centralized inventory encompassing: AI AgentsMCP ServersAI ApplicationsAI ToolsLLMs and Foundation ModelsPrompts and Prompt LibrariesAI Services and APIs
• •Ensure the registry serves a dual purpose: Discovery Platform for users to identify approved AI assets and capabilities. Governance Platform for managing ownership, compliance, risk, and lifecycle controls.
• •Define metadata standards, ownership models, classification schemes, and governance workflows.
• •Establish inventory management processes across business units and technology functions.

AI Agent Governance

• •Define governance standards and controls for Agentic AI and autonomous workflows.
• •Establish requirements around auditability, explainability, human oversight, monitoring, and accountability.
• •Develop governance guardrails for multi-agent ecosystems and interactions with enterprise systems.
• •Create standards for onboarding, certification, and production deployment of AI agents.

AI Evaluation & Testing Framework

• •Design and implement an enterprise AI Evaluation Framework covering: Functional testingAccuracy and performance validationHallucination testingRisk and compliance validationSecurity testingPrompt testing and evaluationBias and fairness assessmentAgent behavior validationBusiness outcome measurement
• •Define what must be tested at each stage of the AI lifecycle.
• •Establish evaluation metrics, benchmarks, acceptance criteria, and approval workflows.
• •Enable continuous monitoring and post-production governance processes.

Architecture & Platform Governance

• •Define governance standards for AI solutions leveraging: Claude LLMOpenAI Custom GPTsAWS BedrockAWS AI/ML ServicesAI Agent PlatformsMCP-based ecosystems
• •Define architectural patterns for secure, scalable, and compliant AI deployments.
• •Establish governance controls for model access, prompt management, data usage, and external AI integrations.

Risk, Compliance & Audit

• •Conduct AI governance assessments and risk reviews.
• •Support regulatory compliance initiatives specific to Financial Services.
• •Develop governance dashboards, audit trails, compliance reporting, and executive-level metrics.
• •Maintain comprehensive documentation supporting regulatory, internal audit, and model risk requirements.

Stakeholder Leadership

• •Act as the enterprise subject matter expert for AI Governance and AI Architecture.
• •Drive adoption of governance processes across business and technology teams.
• •Present governance roadmaps, risk assessments, and recommendations to senior leadership and governance committees.

Required Qualifications

• •Bachelor's or Master's degree in Computer Science, Engineering, Data Science, Information Systems, or a related field.
• •10+ years of experience in Enterprise Architecture, Technology Governance, AI/ML Platforms, or Risk Management.
• •5+ years of experience designing and implementing AI Governance or Model Governance frameworks.
• •Demonstrated experience building enterprise inventories, asset registries, governance repositories, or catalog solutions.
• •Strong knowledge of: AI GovernanceResponsible AIAI Risk ManagementModel Lifecycle ManagementAgentic AI GovernanceEnterprise Architecture
• •Experience working with: Claude LLMOpenAI / Custom GPT implementationsAWS Cloud Services (Bedrock, SageMaker, Lambda, IAM, etc.)
• •Hands-on experience defining evaluation methodologies for LLMs, AI agents, and GenAI applications.
• •Experience defining governance controls across AI agents, applications, and enterprise AI platforms.
• •Strong understanding of data privacy, cybersecurity, and regulatory requirements within Financial Services.
• •Excellent communication, stakeholder management, and leadership skills.

Preferred Qualifications

• •Experience building an enterprise AI Registry from concept through implementation.
• •Experience governing Agentic AI ecosystems, MCP servers, AI marketplaces, or AI service catalogs.
• •Familiarity with model risk management (MRM) frameworks used within Financial Services organizations.
• •Knowledge of banking, asset management, wealth management, capital markets, or insurance domains.
• •Experience with AI observability, monitoring, evaluation, and governance tooling.
• •AWS Solutions Architect, AWS Machine Learning Specialty, TOGAF, or equivalent professional certifications.
• •Experience supporting enterprise AI transformation initiatives and governance operating models at scale.
• •Understanding of emerging industry standards related to AI governance, responsible AI, and agent governance.

• Pay:
• The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Fractal, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is: $180,000 to $200,000 Yearly. In addition, you may be eligible for a discretionary bonus for the current performance period.

• Benefits:
• As a full-time employee of the company or as an hourly employee working more than 30 hours per week, you will be eligible to participate in the health, dental, vision, life insurance, and disability plan in accordance with the plan documents, which may be