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I am an AI Full-Stack Engineer with 4+ years of experience building production-grade distributed systems in financial services. My core strengths are Go (Golang) and Python across microservices, database design and optimization, cloud platforms (AWS, Azure, GCP), and containerized deployments. I have a proven track record delivering scalable AI and ML backend solutions with high reliability in fast-paced, international team environments. I enjoy turning cutting-edge AI research into production-ready solutions, optimizing system performance, and collaborating with cross-functional teams to drive business impact. I focus on reliability, scalability, and clear communication to translate complex ideas into practical engineering outcomes.…I am an AI Full-Stack Engineer with 4+ years of experience building production-grade distributed systems in financial services. My core strengths are Go (Golang) and Python across microservices, database design and optimization, cloud platforms (AWS, Azure, GCP), and containerized deployments. I have a proven track record delivering scalable AI and ML backend solutions with high reliability in fast-paced, international team environments. I enjoy turning cutting-edge AI research into production-ready solutions, optimizing system performance, and collaborating with cross-functional teams to drive business impact. I focus on reliability, scalability, and clear communication to translate complex ideas into practical engineering outcomes.

Ethan Lew

AI Engineer, Full Stack Developer, Data Scientist, +2

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I am an AI Full-Stack Engineer with 4+ years of experience building production-grade distributed systems in financial services. My core strengths are Go (Golang) and Python across microservices, database design and optimization, cloud platforms (AWS, Azure, GCP), and containerized deployments. I have a proven track record delivering scalable AI and ML backend solutions with high reliability in fast-paced, international team environments. I enjoy turning cutting-edge AI research into production-ready solutions, optimizing system performance, and collaborating with cross-functional teams to drive business impact. I focus on reliability, scalability, and clear communication to translate complex ideas into practical engineering outcomes.…I am an AI Full-Stack Engineer with 4+ years of experience building production-grade distributed systems in financial services. My core strengths are Go (Golang) and Python across microservices, database design and optimization, cloud platforms (AWS, Azure, GCP), and containerized deployments. I have a proven track record delivering scalable AI and ML backend solutions with high reliability in fast-paced, international team environments. I enjoy turning cutting-edge AI research into production-ready solutions, optimizing system performance, and collaborating with cross-functional teams to drive business impact. I focus on reliability, scalability, and clear communication to translate complex ideas into practical engineering outcomes.

Available to hire

I am an AI Full-Stack Engineer with 4+ years of experience building production-grade distributed systems in financial services. My core strengths are Go (Golang) and Python across microservices, database design and optimization, cloud platforms (AWS, Azure, GCP), and containerized deployments. I have a proven track record delivering scalable AI and ML backend solutions with high reliability in fast-paced, international team environments.

I enjoy turning cutting-edge AI research into production-ready solutions, optimizing system performance, and collaborating with cross-functional teams to drive business impact. I focus on reliability, scalability, and clear communication to translate complex ideas into practical engineering outcomes.

Skills

Experience Level

Expert

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Language

English

Fluent

Work Experience

Gen AI Engineer at Banking Industry

January 1, 2024 - Present

Current role focusing on generative AI solutions for the banking sector, including designing AI architectures, evaluating AI services, and delivering cloud-enabled AI applications.

AI Engineer at Saratix AI Sdn. Bhd.

January 1, 2024 - September 9, 2025

Designed cloud-based and hybrid AI architectures; conducted research using Microsoft Azure AI Services for enterprise banking solutions; built applications with Power Platform; implemented transformer models (GPT-3, LLaMA, BERT) and Gemini/Claude via Azure OpenAI for financial use cases. Performed prompt engineering and fine-tuning with notable improvements; developed OCR/NLP/chatbot features and containerized deployments using Docker and Kubernetes.

Gen AI Engineer at Banking Industry

January 1, 2024 - Present

Designing and implementing Gen AI solutions for banking clients. Built AI architecture diagrams (cloud-based and hybrid-based) and conducted research using Microsoft Azure AI services (Azure OpenAI, Cognitive Services) for enterprise banking scenarios. Leveraged GPT, Claude, and Gemini family models for financial use-cases; applied prompt engineering and model fine-tuning to improve domain-specific accuracy. Implemented model evaluation frameworks to monitor bias and fairness; utilized GitHub Copilot for development and Git for version control. Translated recent AI research into production-ready solutions in collaboration with cross-functional teams.

AI Engineer at SARATIX AI Sdn. Bhd.

January 1, 2024 - September 9, 2025

Designed AI architecture diagrams (cloud-based & hybrid-based) and conducted research using Microsoft Azure AI services for enterprise banking solutions. Developed applications using Microsoft Power Platform (Power Apps, Power Automate, Microsoft Copilot) and implemented GPT-4, Claude, and Gemini models for financial use cases. Applied prompt engineering and model fine-tuning to achieve improvements in domain-specific banking tasks. Implemented model evaluation frameworks with bias and fairness metrics, leveraging GitHub Copilot for development and Git for version control. Translated recent AI research into production solutions and collaborated with cross-functional teams to deliver compliant AI systems. Built scalable AI solutions using containerization (Docker, Kubernetes) and serverless deployment; led OCR, data crawling, and NLP chatbot initiatives using Python, TensorFlow, and PyTorch.

AI Full-Stack Engineer at Maybank

May 1, 2025 - Present

Architected a multi-agent loan automation system with a Go backend orchestrating LangGraph agents for concurrent financial data retrieval, modeling, and risk assessment across distributed microservices, reducing loan processing time from 3 days to 1 day for 500+ monthly applications. Designed a centralized evaluation system with LangGraph where domain-expert AI agents evaluate distinct quality metrics, with a Next.js frontend, Redis caching, PostgreSQL, and RESTful APIs. Developed enterprise reference architectures for AWS and Azure, establishing standardized blueprints with security best practices and cloud design patterns, reducing EA approval time by 70%. Implemented backend services for enterprise apps using Microsoft Power Platform, integrating Azure OpenAI, Claude, and Gemini APIs for automated document processing and workflow automation. Improved system quality through structured code reviews, testing, staged rollouts, and proactive production monitoring.

AI Engineer at Saratix AI Sdn. Bhd.

January 1, 2022 - January 1, 2025

Engineered end-to-end LLM optimization pipelines from CUDA kernels to Kubernetes deployments, increasing GPU utilization from 60% to 85% and reducing inference latency by 35%. Built production transcription system processing 600+ meetings monthly with 95% accuracy using a distributed FastAPI backend, RabbitMQ, and AWS EC2, cutting manual effort by 90%. Designed and optimized PostgreSQL, MongoDB, and Redis schemas to support high-throughput services, improving query performance and latency. Trained and optimized LLMs via LoRA/QLoRA fine-tuning and RAG pipelines for enterprise chatbot products; reduced model size by 50% and infrastructure costs by 40% through custom CUDA kernels and GPTQ/AWQ quantization. Led containerized deployments with Docker/Kubernetes, CI/CD, and Terraform; owned end-to-end backend architecture, caching, messaging, and monitoring.