Mike Yip

Cloud & AI Solution Architect leading multi‑cloud solution design and architecture evaluations across OCI, AWS and Azure, with a focus on secure, scalable cloud platforms supporting enterprise data and analytics workloads. Focused on defining cloud‑first reference architectures, aligning cloud networking, connectivity, governance and data‑platform design to support regulated, enterprise‑scale environments. Key Responsibilities • Designed multi‑cloud reference architectures covering cloud networking, hybrid connectivity, API gateways, orchestration and governance across OCI, AWS and Azure. • Defined cloud‑based data platform architectures (data lake / warehouse) within multi‑cloud environments, including governance zones, data‑product boundaries and semantic modelling approaches. • In the domain of data platform architecture, I specialize in designing and implementing cloud-native data pipelines, leveraging services such as Azure Fabric, Azure Event Hubs and AWS Kinesis to enable scalable and reliable data solutions. • Established cloud security and privacy patterns aligned with PDPO, including access control, data masking, auditability and cross‑cloud traceability. • Worked across cloud and data domains to ensure platform interoperability, scalability and operational readiness rather than tool‑specific optimisation. Selected architecture case studies demonstrating how emerging AI workloads are incorporated into enterprise multi‑cloud platforms: PROJECT 1 — Enterprise AI Platform Architecture (GenAI Workloads on Multi‑Cloud Reference Design AWS / Azure / GCP / OCI / Alibaba) PROJECT 2 — Secure AI Workflow Architecture for Regulated Environments Outcomes • Delivered multi‑cloud and Data architecture blueprints enabling consistent platform design and informed cloud‑adoption decisions. • Improved cloud platform traceability, security posture and interoperability across enterprise cloud ecosystems.

Acted as Private Cloud & GenAI platform architect for a greenfield, on‑prem private cloud initiative supporting a government department, responsible for defining a secure, production‑ready platform architecture for containerised enterprise workloads and governed GenAI adoption in private cloud environment. • Owned the end‑to‑end architecture design of a government‑grade private cloud platform, defining cluster topology, security boundaries, environment separation and operational controls aligned with data‑residency and regulatory requirements. • Designed a production‑ready OpenShift‑based container platform from scratch, establishing CI/CD integration, workload isolation and platform governance suitable for long‑term enterprise operation. • Defined governed GenAI workload architectures deployed fully on‑prem, covering document ingestion, chunking strategies, embedding pipelines, vector‑based retrieval (RAG) and LLM inference using enterprise‑approved, private cloud‑hosted models. • Established secure, non‑intrusive integration patterns between the GenAI solution and existing systems, enabling side‑by‑side enhancement without impacting legacy Java applications or newer web services. • Acted as the architecture coordination point between the government client and multiple vendors, translating business and regulatory requirements into practical, supportable platform and solution designs. Selected Architecture Case Studies: PROJECT 3 — Governed GenAI Workflow Architecture with Human‑in‑the‑Loop Control PROJECT 4 — Enterprise Vector Retrieval Architecture Pattern PROJECT 5 — LLM Orchestration Architecture for Enterprise Chat Interfaces Outcome Delivered a production‑ready private cloud and governed AI architecture blueprint, enabling controlled adoption of AI capabilities in a regulated environment without compromising security, compliance or system stability.

Led system modernisation and government cloud architecture migration, security compliance and platform upgrades for the SWD VISE system. Serving as the solution architect for GCIS-based deployment and integration. Delivered architecture refresh, privacy alignment and API redesign in collaboration with government infrastructure teams and vendors. Key Responsibilities • Directed VM migration to GCIS, defining cloud infrastructure architecture, network bandwidth and security zoning requirements. • Ensured compliance with SRAA, PIA, IAM Smart API, WAF and government security/privacy standards. • Modernised application and system architecture from legacy frameworks to an API-driven design, enabling structured and unstructured data ingestion with governed metadata management. • Redesigned web and RESTful API services supporting cross‑system data exchange; integrated IAM Smart for identity and access control. • Defined security controls, addressed audit findings and implemented remediation actions. • Worked with stakeholders on requirements validation, technical walkthroughs, UAT planning and rollout readiness. Outcome Strengthened government cloud security posture, compliance alignment and operational stability on GCIS.

Architected and delivered large-scale enterprise systems and data platforms across a multi-year engagement, evolving from core ERP and application development into enterprise data and solution architecture roles for public-sector clients, including territory-wide law-enforcement systems. Phase 1 – Oracle Financial ERP Systems Foundation • Delivered and supported Oracle-based ERP and financial systems Phase 2 – Large-Scale Web & Application Modernisation • Contributed to large-scale web system modernisation, application integration and secure high-availability design. Phase 3 — Data Platform • Led the design and delivery of enterprise data-warehouse and analytics platforms supporting territory-wide police case management systems. • Architected data-ingestion, transformation and reporting pipelines enabling operational and investigative analytics. Key Responsibilities • Designed enterprise data-architecture roadmaps covering ingestion, transformation, governance, lineage and analytics enablement for large-scale public-sector platforms. • Delivered secure, governed data-exchange architectures and directed ETL/ELT frameworks with metadata standards, traceability and operational governance. • Established data quality, privacy and security policies and conducted architecture reviews to ensure performance, resilience and regulatory alignment. --- Outcomes • Delivered and modernised multiple large-scale BI and data platforms supporting mission-critical public-sector operations. • Enabled cross-department data sharing, improved operational insight and laid architectural foundations for later cloud and AI adoption.

Delivered enterprise solutions across Oracle Financials, data‑integration workflows and BI reporting for Finance, Operations and PRC branches. Built foundational expertise in ERP, integration and data architecture supporting later progression into cloud and AI architecture roles. Key Responsibilities • Re‑engineered GL/AP processes including COA restructuring, consolidation logic and approval flows to improve accuracy and reporting timeliness. • Automated supplier‑payment file exchange with banking systems, reducing manual reconciliation and accelerating month‑end closing. • Designed and managed interfaces between Oracle Financials and U8/UFIDA systems for costing, journal and invoice‑data transfers. • Built PRC‑compliant GL/AP interfaces supporting risk management and branch‑level transparency. • Directed POS‑to‑financial/analytics integration enabling real‑time sales visibility. • Designed Cognos BI data models and reporting layers supporting dashboards, profitability and operational reporting. Cloud‑Ready Development • Achieved Oracle Fusion ERP, Fusion SCM and Fusion Agent certifications, forming the foundation for extending legacy ERP expertise into OCI, Fusion Cloud, modern data platforms and AI‑enabled workflows.