Singapore 🇸🇬
Senior AI/ML leader with 7+ years at AWS, having supported 50–75 enterprise customers bringing Agentic AI and Generative AI solutions to production, contributing to hundreds of millions in pipeline. Specialised in translating complex technical capabilities into go-to-market strategies and thought leadership that drive measurable adoption at scale.
Regional Leadership: Leading GenAI/ML initiatives across the ASEAN region, driving adoption of generative AI and agentic AI solutions for enterprise customers in Southeast Asia.
Market Expansion: Establishing go-to-market strategies tailored to ASEAN markets, working with local teams to accelerate AI/ML adoption across diverse industries and regulatory environments.
Global Go-To-Market Leadership: Owned the worldwide Go-To-Market (GTM) motion for Agentic AI on Amazon SageMaker, driving global strategy and contributing to the product roadmap with customer feedback and open-source frameworks.
Product Strategy & Roadmap: Served as trusted advisor to the General Manager of Low-Code/No-Code ML, collecting customer feedback and collaborating with Product Managers to shape product roadmap. Worked with the broader SageMaker AI Service Team validating roadmap items and suggesting new features and products to build.
Community Leadership: Led a community of 100 Low-Code/No-Code ML Champions worldwide, supporting global opportunities. Worked with the Service Team for Amazon SageMaker Canvas, AWS's top LCNC ML tool, on prioritizing items for the product roadmap.
Content Creation & Thought Leadership: Created four public-facing workshops and authored dozens of AWS ML blogs, advancing thought leadership and community adoption globally.
Speaking Engagements: Delivered breakout sessions at 4 consecutive AWS re:Invent conferences (owning at least one session each year), presented at multiple AWS Summits across 8 cities (Paris, London, Amsterdam, Zurich, Milan, Athens, Madrid, Dubai), featured twice in AWS Online Tech Talks, and participated in the Italian AWS podcast.
Enterprise Solutions: Architected complex AI-driven solutions for top AWS customers worldwide, demonstrating measurable impact through technical excellence and strategic guidance.
Regional Expertise: Specialized in Generative AI and Machine Learning solutions for the Benelux region (Belgium, Netherlands, Luxembourg), establishing the foundation for AI/ML adoption in the region.
Customer Success: Worked directly with enterprise customers to architect and implement scalable AI/ML solutions, focusing on emerging generative AI technologies and traditional ML workloads.
Market Development: Built relationships with key customers and partners in the Benelux market, contributing to the growth of AWS AI/ML services adoption in the region.
Worked as Solutions Architect helping customers architect and build scalable, secure, and cost-effective cloud solutions on AWS. Specialized in machine learning and data analytics workloads.
Exploring how to integrate predictive ML models with AI agents using Amazon SageMaker and MCP for enhanced decision-making capabilities.
Read ArticleComprehensive guide on scaling ML operations for organizations managing large numbers of models across diverse use cases.
Read ArticleDemonstrating how business users can fine-tune and deploy large language models using no-code tools for domain-specific applications.
Read ArticleStep-by-step tutorial on creating intelligent customer support solutions using Amazon Bedrock AgentCore for enhanced customer experience.
Read ArticleExploring how to enhance AI agents by integrating machine learning models using Amazon SageMaker AI and Amazon Bedrock AgentCore platform.
Read ArticleComprehensive guide on integrating Amazon SageMaker AI capabilities with the Strands Agents Python SDK for building intelligent AI applications.
Read ArticleA hands-on guide to training, deploying, and orchestrating AutoGluon models with SageMaker Python SDK v3.
Mar 17, 2026Three progressively sophisticated approaches to Non-Technical Loss (NTL) detection, all built on Amazon SageMaker.
Mar 16, 2026Five lessons learned following the path from raw data to end user in production retrieval systems.
Feb 24, 2026Migrated entire DIY agents workshop to SageMaker Python SDK v3, updating 8 notebooks with new patterns for ModelTrainer, boto3 integration, and modern SDK architecture.
View PR #163Added support for Amazon SageMaker AI endpoints as Model Provider, enabling developers to use SageMaker-hosted models with the Strands Agents framework.
View PR #176Fixed SageMakerEmbedding class to improve compatibility and reliability when using Amazon SageMaker endpoints for embeddings.
View PR #10778Reference architectures, standard patterns, labs, end-to-end workshops, and reproducible examples across multiple repositories including:
Breakout session exploring how model customization enables agents that better understand business context and provide more accurate, domain-specific responses.
Demonstrating how to accelerate AI agent development using integrated workflows between Amazon SageMaker Studio and Amazon Bedrock AgentCore.
Live demonstration of Amazon SageMaker Canvas, showcasing how business users can build and deploy machine learning models using a no-code interface.
Feel free to reach out for collaboration opportunities, speaking engagements, or technical discussions about AI/ML and cloud architecture.