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Janq-Liang “Max” Tsai
Transforming enterprise operations through AI-driven platforms and production-ready digital transformation
—accelerating the path to scalable, ready-to-market capabilities
Specializing in Agentic AI platforms, intelligent systems,
and enterprise-scale automation
What I Build
Agentic AI platforms and multi-agent systems • Enterprise AI governance and operating models • Production-ready digital platforms • Autonomous workflows and intelligent service systems • High-performing teams
80%
80%
Operational Workload Reduction
AI-Driven Operational Transformation
Redesigned enterprise workflows using agentic AI platforms, integrating LLM orchestration and automation to transform multi-step processes into intelligent, autonomous operations.
30%
30%
Technology Cost Optimization
Enterprise Platform Modernization
Modernized enterprise platforms through API-first architecture, iPaaS integration, and automation—reducing total cost of ownership while improving scalability and performance.
25%
25%
Operational Efficiency Gain
Digital Workflow Optimization
Reengineered enterprise workflows, embedding automation and data-driven decisioning to improve service delivery, cycle time, and user experience.
25k+
25k+
Users Supported at Scale
Enterprise AI Platform Delivery
Designed and deployed enterprise AI and digital service platforms supporting 25,000+ users in a regulated environment.
Signature Case Studies
Signature Case Studies
Enterprise Agentic AI Platform
Enterprise Agentic AI Platform
Overview
Built an enterprise agentic AI platform transforming service delivery into autonomous, AI-driven operations across 25,000+ users. Bulldog Genie is an enterprise-grade agentic AI platform designed to transform service delivery through intelligent, multi-agent automation. The platform integrates conversational AI, retrieval-augmented generation (RAG), and workflow orchestration to enable autonomous, scalable digital services.
Problem
Enterprise service delivery relied heavily on manual, multi-step processes across disconnected systems, resulting in inefficiencies, delays, and limited scalability. Existing automation approaches were fragmented and unable to support intelligent decision-making or adaptive workflows.
Approach
Led the design and deployment of a unified agentic AI platform that integrates LLM orchestration, enterprise data retrieval, and workflow automation. Established reusable platform patterns enabling teams to deploy AI-powered solutions while maintaining governance, security, and operational control.
Architecture
Multi-agent system architecture with LLM orchestration
Retrieval-Augmented Generation (RAG) for enterprise knowledge access
API-first and event-driven integration across enterprise systems
Workflow automation and orchestration layer
Observability and monitoring for AI decision traceability
Governance & Risk
Implemented AI governance aligned with NIST AI RMF
Established observability frameworks for auditability and explainability
Enabled human-in-the-loop controls for critical decision points
Ensured compliance with data security and privacy standards
Outcomes
Achieved up to 80% reduction in manual workload
Improved service resolution time and operational efficiency
Scaled across enterprise workflows supporting 25,000+ users
Established foundation for enterprise-wide AI adoption
Key Takeaway
Demonstrated how agentic AI can move organizations from task automation to autonomous, intelligent operations at enterprise scale.
Automated University — Enterprise Workflow Transformation
Automated University — Enterprise Workflow Transformation
Overview
The Automated University initiative reimagined enterprise operations by digitizing and automating workflows across academic and administrative domains, creating a unified, scalable digital service environment.
Problem
Manual and semi-automated workflows created inefficiencies, redundancy, and inconsistent service experiences. Systems were siloed, limiting integration and real-time data exchange.
Approach
Led enterprise-wide workflow transformation leveraging API-first architecture, iPaaS (Boomi), and automation frameworks. Integrated ERP, CRM, and other enterprise systems to enable seamless data flow and process orchestration.
Architecture
API-first and microservices-based integration
iPaaS (Boomi) for system interoperability
Workflow automation across business processes
Data integration enabling real-time operations
Governance & Risk
Established standards for integration, security, and data governance
Ensured compliance with institutional and regulatory requirements
Implemented change control and release management processes
Outcomes
Delivered 25% operational efficiency gain
Reduced duplication and manual processing
Improved service delivery and user experience
Enabled scalable, mobile-first digital services
Key Takeaway
Proved that enterprise workflow transformation requires integrated platforms, not isolated automation, to achieve sustainable efficiency and scalability.
Innovation & Workforce Development Platform
Innovation & Workforce Development Platform
Overview
Hub of Digital Transformation and Innovation (DXIHub) is a digital transformation and innovation incubator designed to accelerate solution development while building a sustainable talent pipeline through hands-on student engagement.
Problem
Organizations lacked both the capacity to rapidly prototype innovative solutions and a pipeline of talent equipped with modern AI and digital skills.
Approach
Founded and scaled DXIHub as a cross-functional innovation environment combining engineering, product thinking, and applied AI development. Created structured internship and mentorship programs aligned with real-world projects.
Model
Cross-functional teams of students and professionals
Rapid prototyping and iterative development
Integration of AI, data, and digital platforms
Mentorship and workforce development programs
Governance & Execution
Established program structure, delivery standards, and project governance
Aligned initiatives with institutional priorities and strategic goals
Partnered with industry and academic stakeholders
Outcomes
Delivered 20+ AI and digital solutions
Provided 150+ internship opportunities
Accelerated innovation and solution delivery
Built a sustainable pipeline of AI-ready talent
Key Takeaway
Demonstrated that innovation and workforce development can be integrated into a single operating model that drives both organizational value and long-term capability building.
Leadership, Governance & Operating Model
Leadership, Governance & Operating Model
Enterprise Leadership
Enterprise Leadership
Lead enterprise AI, digital transformation, and governance across mission-critical platforms—operating as a system-level decision maker in a regulated environment.
Direct cross-functional teams across engineering, architecture, accessibility, and digital services
Partner with executive leadership (CIO, cabinet, academic and administrative leaders) to align technology strategy with institutional priorities
Build and scale innovation programs (DXIHub) developing talent pipelines and accelerating solution delivery
Oversee vendor strategy, platform investments, and multi-cloud ecosystems to optimize cost, performance, and long-term value
Enterprise Governance Leadership
Enterprise Governance Leadership
Chair enterprise governance bodies that define how technology, AI, and risk are managed across the institution.
Chair, AI Services & Technology Innovation Committee
Lead enterprise AI strategy, evaluation, and adoption—establishing governance, standards, and responsible AI practices
Chair, Change Control Board (IT Governance)
Govern enterprise technology releases, operational risk, and production readiness in a regulated environment
Chair, IT Governance — Campus Applications Architecture
Align enterprise architecture, integration strategy, and platform modernization across systems
Chair, Web & Mobile Accessibility Governance
Lead institutional accessibility strategy and compliance (ADA / Title II), ensuring inclusive digital services
Operating Model & Transformation Execution
Operating Model & Transformation Execution
Design and operationalize enterprise digital and AI transformation as a scalable, governed system—not isolated initiatives.
Established an AI and Digital Transformation operating model integrating platform strategy, governance, and delivery
Implemented API-first, event-driven, and iPaaS (Boomi) architectures enabling enterprise interoperability
Embedded AI governance aligned to NIST AI RMF, ensuring trust, auditability, and compliance
Built production-ready AI platforms (LLMs, RAG, multi-agent systems) integrated into enterprise workflows
Enabled continuous delivery through DevSecOps, CI/CD, and release governance models
Operating at the intersection of executive leadership, AI-enabled transformation, and enterprise architecture—translating strategy into scalable, governed, and production-ready systems.
Career Evolution
Career Evolution
Enterprise Architecture Foundation
Enterprise Architecture Foundation
~ 2016
Built deep technical expertise across enterprise systems, infrastructure, and integration architecture in large-scale, regulated environments.
Designed and operated ERP, CRM, and enterprise data platforms
Led integration architecture, APIs, and middleware ecosystems
Implemented IAM, security frameworks, and high-availability systems
Established scalable foundations for data, analytics, and future AI capabilities
Digital Transformation & Innovation Leader
Digital Transformation & Innovation Leader
2016 - 2022
Expanded into enterprise transformation leadership, driving modernization of workflows, platforms, and service delivery models.
Led digital transformation initiatives across academic and administrative domains
Introduced automation, API-first architecture, and cloud-based services
Founded DXIHub, building innovation pipelines and workforce development programs
Delivered measurable improvements in efficiency, service delivery, and user experience
Built a multi-year innovation portfolio spanning AI, cloud, cybersecurity, blockchain, XR/VR, and student success initiatives—supported through grants, sponsorships, and institutional incubation.
Executive AI & Platform Leader
Executive AI & Platform Leader
2022 – Present
Operating at an executive level, leading enterprise AI strategy, platform architecture, and governance across mission-critical services.
Defined and executed enterprise AI and automation strategy
Architected and deployed agentic AI platforms and multi-cloud infrastructure
Established AI governance aligned with NIST AI RMF and regulatory standards
Led enterprise platforms supporting 25,000+ users in a regulated environment
Progression from enterprise architecture to executive AI leadership—expanding scope from systems to platforms to institution-wide operating models.
Recognition & Influence
Recognition & Influence
Recognition
Recognized for advancing enterprise AI, digital transformation, and workforce development at institutional and national levels.
AWS Education Champion — national recognition for AI and cloud leadership
CSU Distinguished Innovator — systemwide recognition for digital transformation leadership
Speaking & Publications
EDUCAUSE Presenter — including Beyond Spreadsheets: How AI is Teaching Higher Ed New BI Tricks
Speaker on enterprise AI, digital transformation, and platform architecture
Teaching & Workforce Development
Faculty, Build AI as a Software Engineer
Founded and led DXIHub, mentoring 100+ emerging technologists and developing 20+ applied solutions
Founding Director, Workforce Development — WITH-Cyber IT, Cybersecurity & AI Internship Program
Grants & Sponsored Innovation
Led grant-funded innovation initiatives across AI, cloud, cybersecurity, immersive technologies, and digital transformation
Directed sponsored pilots and applied research programs with AWS, CSU, and cross-sector partners
Converted external funding into scalable prototypes, institutional capabilities, and workforce development outcomes
Executive Vision & Focus
Executive Vision & Focus
I focus on building the next generation of enterprise operating models where AI is embedded into core systems, workflows, and decision-making—moving organizations from fragmented digital efforts to intelligent, autonomous, and continuously improving platforms.
My work centers on scaling agentic AI, modernizing enterprise platforms, and establishing governance frameworks that enable innovation while ensuring trust, security, and compliance in regulated environments.
I am particularly focused on advancing:
Agentic AI platforms and multi-agent systems for enterprise-scale automation
AI-enabled operating models that integrate workflows, data, and decision intelligence
Governed AI adoption, embedding risk management, observability, and responsible AI practices
Platform-based transformation, enabling organizations to move from projects to scalable capabilities
Operating at the intersection of executive leadership, AI-enabled transformation, and enterprise architecture—translating strategy into scalable, governed, and production-ready systems.
Operating at the intersection of executive leadership, AI-enabled transformation, and enterprise architecture—translating strategy into scalable, governed, and production-ready systems.
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