Dennis Pang Jia Wang
Senior AI Engineer | AI Solution Architecture
dennis000626@gmail.com | linkedin.com/in/dennispjw | Kuala Lumpur, Malaysia
Summary
AI and Data Solutions Professional with expertise in Agentic AI, enterprise AI architecture, LLM-enabled analytics, data engineering, and intelligent automation. Experienced in architecting scalable AI and data solutions, designing multi-agent workflows, RAG-enabled validation, conversational BI platforms, and production ELT/ML pipelines that deliver measurable business value. Proven leadership coordinating technical delivery across 9-member cross-functional teams and bridging business stakeholders with engineering teams.
Technical skills
AI and Generative AI: Agentic AI, LLM Applications, RAG, LangChain, LangGraph, Crew, Prompt Engineering, Structured Outputs, Human-in-the-Loop
AI Architecture: Multi-Agent Orchestration, Supervisor-Worker Patterns, Planner-Executor Design, MCP Tools, SQL
Machine Learning: Predictive Modelling, Feature Engineering, Model Evaluation, Optimization, XGBoost, KNN, ARIMA, TensorFlow
Data Engineering: Python, SQL, ELT/ETL Pipelines, Data Preprocessing, ClickHouse, Data Warehousing, Data Quality
Cloud and MLOps: AWS, Amazon Bedrock AgentCore, Lambda, EventBridge, S3, API Gateway, QuickSight, OCI, Azure AI, MLOps, CI/CD, Monitoring
Automation and Analytics: n8n, UiPath, REST APIs, Webhooks, SharePoint, Microsoft Teams, Power BI, Qlik Sense
Governance and Delivery: AI Governance, Responsible AI, Cloud Security, Agile Delivery, Scrum, Stakeholder Management, Technical Coordination, Solution Delivery
Languages: English (Proficient), Chinese (Native), Malay (Proficient)
Professional experience
Analytics Specialist | Quandatics (M) Sdn. Bhd.
May 2025 - Present- Designed an HR travel multi-agent automation architecture using n8n, Microsoft Teams, RAG policy validation, SharePoint audit records, APIs, structured JSON, and human-in-the-loop approvals to automate eight core workflows, designed to reduce manual coordination by up to 95%.
- Engineered request-state management, revalidation, idempotency, and Saga-style rollback concepts for price changes, partial booking success, refunds, and booking modifications, designed to reduce manual exception handling by up to 90%.
- Designed an AWS conversational AI and agentic BI platform using Bedrock AgentCore, Lambda, EventBridge, RDS SQL Server, S3, API Gateway, Cognito, QuickSight, MCP, RAG, and SQL generation toward two paid pilots and an RM30k MRR target.
- Delivered RapidMiner data engineering and analytics work across Python, SQL, AWS, ClickHouse, Qlik Sense, Power BI, KNN, XGBoost, and ARIMA, processing 10M+ records and improving forecasting accuracy by 80%.
- Automated Excel, PDF, Word, ERP, email, and master-tracker workflows with UiPath, improving efficiency by up to 90% and reducing processing time by 80%.
Finance Transformation and Digitalisation Intern | Quandatics (M) Sdn. Bhd.
Nov 2024 - May 2025- Supported Oracle NetSuite Saved Searches and SuiteAnalytics for ERP migration and e-Invoice reporting.
- Migrated 1,200+ AutoCount financial records and built reporting for AP, AR, managers, CFO, and CEO stakeholders.
- Reduced report preparation effort by up to 70% and supported same-day reporting across 10+ stakeholders.
Education
Bachelor of Computer Science (Honours) in Data Science | Tunku Abdul Rahman University of Management and Technology
Jun 2022 - Jun 2025CGPA 3.36. Final-year project: Airbnb New User Prediction System.
Diploma in Computer Science | Lincoln University College
May 2019 - May 2022CGPA 3.75.
Leadership and achievements
- Led a six-member cross-functional RapidMiner ML project team through Scrum ceremonies, sprint planning, mentoring, and tracking.
- Coordinated Agile delivery across engineering, management, client, business, and stakeholder groups.
- Gold Award for Graduate Attributes with 1,615+ cumulative points.
- Deputy Vice Chairperson, Computer Science Society; led 23 committee members.
- President, Faculty of Computing & Information Systems Student Representative Council.
Publication and links
- Artificial Intelligence-Powered Breast Cancer Prognosis: Optimizing Deep Learning with Image Normalization. DOI: 10.3390/engproc2026128049.
- GitHub: github.com/dennispang626 | Kaggle: kaggle.com/dennispang626.