Enterprise Architect (AI Governance)

Enterprise Architect (AI Governance), Sacramento, CA, US
Enterprise Architect (EA) Consultant (EA Operations & EA Office Stand-Up)
Scope Of Work
Seeking a leased employee EA Consultant to lead the tactical execution of enterprise architecture (solutions guidance, standards enforcement, architectural runway) while designing and standing up the EA Office—integrated with PMO and BRM—within a unified Strategy & Governance department. Establish shared services for intake orchestration, AI and data architecture enablement, and financial analytics, and co-own process automation and AI enablement for project managers and shared services specialists.
Key Responsibilities

Tactical EA (≈50%)
Solution Architecture & Guidance: Produce solution intents, architecture decision records (ADRs), and reference architectures aligned to enterprise standards.
Standards & Patterns: Curate cloud, data, integration, security, and AI/ML patterns (e.g., Azure reference implementations, data mesh vs. warehouse).
Architecture Governance: Chair/coordinate Architecture Review Board (ARB); manage exceptions, waivers, and technical debt logs.
Road mapping: Maintain capability maps and technology roadmaps; ensure fit to business strategy and PMO portfolio plans.
Risk & Compliance: Embed security/privacy by design; align with regulatory and data governance requirements.
Vendor/Tool Evaluation: Conduct comparative assessments; ensure interoperability and cost-effectiveness.
Asset Management: Optimize and maintain the CMDB.
Change Management: Participate in Change Management Review Boards to assess and validate.
Software Purchase Evaluation: Evaluate software purchase requests and approve or decline based on SMUD policies including security and inventory review.
Project Technology: Evaluate and validate software proposed in overall solutions for specific projects.
Architecture Design and Strategy: Develop and maintain enterprise architecture frameworks, including business capability maps, technology roadmaps, and IT standards.
System Integration: Evaluate and integrate IT systems, ensuring interoperability and scalability across applications and platforms.
Stakeholder Collaboration: Work with senior management, technical specialists, and business units to align IT solutions with organizational strategy.
Technology Assessment: Research emerging technologies, recommend architecture changes, and advise on system strategies.
Documentation and Communication: Create and maintain architectural models, transition plans, and business cases for IT investments.
Technology Lifecycle Governance: Manage acquisition request intake, processing, risk management, cybersecurity, procurement, and end-of-life (EOL).
Enterprise Technology Standards: Establish governance to define, develop, and enforce enterprise standards.
EA Office Design, Stand-Up & Integration (≈50%)
Operating Model: Define mission, scope, decision rights (RACI), engagement model with PMO/BRM, and service catalog (e.g., solution reviews, standards stewardship).
Processes: Establish demand-to-delivery lifecycle: intake → triage → architecture initiation → design reviews → ARB → delivery checkpoints → benefits traceability.
Org & Roles: Define EA lead, domain architects (data, app, infrastructure, security), architecture analysts, and integrate shared services.
Tooling: Implement common tooling (e.g., repository for artifacts, ADRs, patterns; Power BI dashboards; Power Automate workflows; M365 Copilot for documentation).
Metrics & Reporting: Develop dashboards to monitor architectural compliance, reuse rates, cycle times, risk posture, and benefit realization.
Change Management: Communicate charter, develop playbooks, onboarding, and training; facilitate adoption across business units.
B1. Shared Services Capability Build-Out

Intake & Triage (Business Analyst): Standardize request forms, categorization, priority scoring, and routing; automate workflows.
AI/Data (AI & Data Analyst): Establish data architecture guardrails, metadata management, data lineage, Master Data Management (MDM), migration frameworks; define AI use-case registry, risk controls, model governance, and prompt libraries.
Value Analytics: Enable intelligent resource optimization for unbiased decision-making, efficient resource allocation, and financial planning. Use variance analysis, forecast models, and link portfolio financials to business outcomes.
B2. Process Automation & AI Enablement (with PMO)

PMO Automation: Automate stage gates, risk logs, RAID logs, status reports, and deliverable reviews; implement Copilot for PMs (agenda drafting, summarization, action item extraction).
Shared Services Automation: Build low-code applications for request triage, architecture review scheduling, and financial reconciliations.
Data-Driven Governance: Integrate portfolio data, architectural compliance data, and financial information into unified Strategy & Governance dashboards.
B3. Stakeholder Management & Communication

Single Face to Business Units: Present integrated services; simplify engagement and escalation pathways.
Executive Reporting: Provide concise, outcome-oriented updates on architecture, health, delivery risks, and transformation value.
DELIVERABLES (Backlog and will be Prioritized once Onboarded)
Foundational Artifacts

EA Office: Charter, Operating Model, Service Catalog, Engagement Playbook
Decision Rights/RACI: RACI matrix, ARB Charter, Exception/Waiver Policy
Standards & Reference Architectures: Cloud, data, integration, security, AI standards
Capability Maps and Roadmaps
Automation & Tools

Intake & Triage App/Workflow: Power Automate / Power Apps
Portfolio & Architecture Dashboards: Power BI
Copilot Enablement: Templates, prompts, and governance guidelines
ADR Repository and Architecture Artifact Library: SharePoint / DevOps
AI & Data

AI Use Case Registry and Model Risk Controls
Data Migration Playbook and Data Governance Guardrails: Lineage, catalog, quality
Reusable Data Pipelines and Integration Patterns
Financial

Automated Budget & Forecast Dashboard: Project cost baselines, benefit tracking models
Experience
MANDATORY REQUIREMENTS

Experience implementing AI and automation in IT governance/processes
Bachelor’s in Engineering / Technical Sciences
15+ years in IT roles, including IT infrastructure, data management, and business systems
Knowledge of cloud platforms, enterprise data management, SQL, and software architecture frameworks
15+ years of experience in enterprise data architecture, data migrations, and data management
15+ years of experience mapping business functionality to IT solutions, assessing risks, and optimizing processes
Demonstrated experience designing and developing Enterprise Governance models to support various IT processes like technology procurement, cybersecurity, AI, project integrations, and business enablement
Strong interpersonal skills to lead teams, facilitate workshops, and present architectural strategies to executives.
Skills & Competencies
Architecture & Technology

Enterprise & Solution Architecture: Capability modeling, architecture runway, ADRs
Cloud & Integration: Event-driven architectures, identity/access management
Data & AI: Data architecture, governance, ETL/ELT, data migration; AI/ML lifecycle, prompt engineering, model governance
Process & Governance

Operating Model Design: Decision rights, organizational design, service catalogs
Portfolio & Demand Management: Intake, triage, prioritization, capacity planning
Architecture Governance: Architecture Review Board (ARB), standards stewardship, exception handling
Automation & Tooling

Power Platform: Power Automate, Power Apps, Power BI
M365 Copilot: Enablement and guardrails
DevOps Tooling: Azure DevOps, Jira for backlogs and documentation
Data Catalog/Lineage Tools: e.g., Microsoft Purview or equivalent
Desirable Qualifications

Certifications in TOGAF, ITIL/COBIT, Azure, SAFe (or equivalent)
Master’s in Engineering / Technical Sciences
Soft Skills & Leadership

Executive communication, changing leadership, stakeholder management
Systems thinking, analytical problem solving, conflict resolution
Coaching/enablement mindset; cross-functional collaboration