AI Governance Arcitect

** 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 Models Prompts 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 testing

Accuracy and performance validation

Hallucination testing

Risk and compliance validation

Security testing

Prompt testing and evaluation

Bias and fairness assessment

Agent behavior validation

Business 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 Services AI 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,…