Senior Software Engineer
About Me
I am a Senior Software Engineer with 12 years of experience building scalable backend systems, AI/ML platforms, and modern full-stack applications. I specialize in delivering real-time decision systems, distributed data pipelines, and cloud-native services using Python, Django, and microservice architectures. My strong full-stack experience with React and TypeScript enables me to develop end-to-end systems from ML inference and data processing to user-facing platforms.
Throughout my career, I have designed and deployed real-time fraud detection models that significantly improve detection accuracy and reduce false positives. I have architected low-latency ML inference services capable of processing millions of financial transaction events daily with minimal scoring latency. I am skilled in building event-driven data pipelines and AI risk decision engines that evaluate onboarding signals, behavioral activity, and transaction patterns for fraud detection.
I have developed RAG-based fraud investigation assistants using LangChain and OpenAI APIs, which have reduced analyst investigation time by approximately 40%. My expertise also includes building NLP pipelines using PyTorch and HuggingFace to extract risk signals from financial documents and compliance reports. I deploy scalable ML services using Docker and Kubernetes on AWS EKS to support high-availability inference workloads.
In addition to backend development, I create React and TypeScript analytics dashboards that enable fraud analysts to monitor alerts, model performance, and risk signals effectively. I collaborate closely with fraud analysts and data teams to continuously improve model features and risk detection accuracy. I also mentor junior engineers to foster their growth and contribute to successful project delivery.
My previous roles include building backend services for Docker Hub container registry infrastructure, contributing to enterprise release automation platforms, and developing fintech platforms such as UnionBank Online banking services. I am proficient in designing REST APIs, relational database schemas, and responsive user interfaces. I am passionate about improving system observability, automating deployment workflows, and enhancing operational monitoring to reduce incident detection time and improve reliability.
Skills
PythonSQLJavaScriptKubernetesJavaReactDockerCI CDTypeScriptTerraformPostgreSQLMentoringKafkaMicroservicesMongoDBRedisGrafanaSpring BootDjangoFlaskAWS S3
Education
Bachelor of Computer Science
Experience
• Designed and developed backend services using Java (Spring Boot), Python for Oscilar AI Risk Decisioning Platform, enabling real-time fraud, credit, and compliance decisioning across financial transactions.
• Built low-latency decisioning services, reducing average response time to under 100ms for transaction risk evaluation across high-volume streaming pipelines.
• Implemented event-driven architecture using Kafka, processing thousands of events per second for real-time ingestion and decisioning workflows.
• Designed and implemented RESTful APIs for transaction processing and risk evaluation, enabling reliable communication between distributed microservices.
• Designed and optimized PostgreSQL schemas for transaction and user data, improving query performance and ensuring consistency for high-volume financial workloads.
• Implemented caching strategies using Redis, reducing data retrieval latency by ~40% and improving performance for real-time decisioning services.
• Developed Python-based services for machine learning and AI workflows using FastAPI, enabling scalable and low-latency model integration.
• Integrated machine learning models using PyTorch, XGBoost, and Scikit-learn, improving fraud detection accuracy and reducing false positives by ~20%.
• Designed microservices-based architecture deployed on Kubernetes, improving scalability, resilience, and supporting high availability across distributed services.
• Built internal dashboards using React and TypeScript, improving analyst efficiency and reducing manual review time for flagged transactions.
• Developed LLM-powered features for case summarization and risk analysis, improving investigation efficiency and reducing manual effort.
• Built retrieval-based pipelines combining real-time and historical data, improving contextual accuracy and explainability of AI-generated insights.
• Leveraged AWS infrastructure for scalable deployment, monitoring, and high availability of real-time decisioning systems.
• Implemented automated testing and CI/CD pipelines, reducing deployment time by ~35% and improving release stability across backend services.
• Leveraged AI-assisted development tools to improve code quality and reduce debugging time across backend and frontend workflows
• Developed backend services using Python for Docker Hub, supporting image repository management and handling thousands of concurrent requests at scale.
• Built responsive frontend features using React and TypeScript, improving usability and reducing page load time by ~25% across key workflows.
• Designed and implemented RESTful APIs, improving response latency from ~200ms to ~120ms for frequently accessed container image operations.
• Implemented asynchronous task processing using Celery, improving background job handling for image processing, notifications, and system workflows.
• Optimized backend services to support high-volume image pull and push operations, improving system throughput and stability under peak traffic conditions.
• Implemented automated testing using PyTest and end-to-end frameworks, reducing regression issues and improving release reliability across deployments.
• Integrated CI/CD pipelines, reducing deployment time by ~40% and enabling faster, more consistent delivery of application updates.
• Leveraged Docker and AWS cloud infrastructure for containerized deployments, improving environment consistency and supporting scalable DevOps workflows.
• Maintained high system availability (>99.9%) through production issue resolution and performance improvements.
Octopus Deploy, Mid-level Developer 02/2018 – 02/2020 | Australia
• Developed backend APIs using Java (Spring Boot) for Octopus Deploy, supporting deployment orchestration across distributed environments.
• Built frontend features using React and TypeScript, improving usability of deployment dashboards and release workflows.
• Migrated legacy services to microservices architecture, reducing deployment failures by ~20%.
• Optimized API performance, reducing response latency from ~100ms to ~40ms for key endpoints.
• Implemented secure communication between services and deployment agents, improving reliability across network environments.
• Collaborated on feature delivery and production issue resolution, improving overall system stability.
Developed fintech platforms including UnionBank Online banking services. Built backend financial services using Java Spring Boot supporting authentication, payments, and banking workflows. Designed REST APIs for banking transactions and financial integrations. Developed responsive React interfaces for banking dashboards and operational tools. Designed relational database schemas supporting secure financial transaction processing.
Developed e-commerce platforms using Django and JavaScript frameworks supporting online retail operations. Implemented payment gateway integrations, order management workflows, and customer account systems. Optimized database queries and caching strategies improving performance during high traffic events.