Jay Chen

Senior Software Architect and Full Stack Engineer with 8+ years of experience designing and delivering enterprise-scale microservices, event-driven architectures, and full-stack applications using .NET Core, C#, React, TypeScript, Node.js, and Python on AWS and Azure. Proven expertise in applying design patterns such as CQRS, Dependency Injection, and Factory patterns to build reliable, scalable, and highly available systems. Experienced in asynchronous programming, multithreading, concurrency control, CI/CD pipeline implementation, containerized deployments with Docker and Kubernetes, and technically mentoring cross-functional development teams across complex, multi-vendor integration environments.

MS Architect / Senior Software Engineer - HotCiti LLC - West Brookfield, MA

(2025-10 - 2026-04)

• Led end-to-end architecture and development of a production-scale web platform, translating complex business requirements into scalable microservices and serverless solutions using .NET Core, React, and TypeScript, deployed on AWS (SageMaker, EKS, Lambda, EC2, S3).
• Designed and implemented event-driven, microservices-based architecture with asynchronous programming patterns, multithreading, and concurrency control for high-availability data workflows handling 1,000+ knowledge base documents.
• Applied CQRS, Dependency Injection, and Aggregator design patterns to build reliable, maintainable backend services, setting high coding standards and best practices across the full development team.
• Implemented CI/CD pipelines with Docker, Kubernetes, and GitHub Actions, ensuring scalable, compliant, and zero-downtime deployments in a fast-paced startup environment.
• Created full-stack React + TypeScript interfaces integrated with RESTful APIs and middleware services, and mentored junior developers across backend, frontend, and architecture workflows to improve team velocity and code quality.

Senior Software Engineer - Beejern - Oklahoma, OK

(2024-07 - 2025-10)

• Designed and delivered multiple enterprise-scale microservices architectures, including event-driven pipelines, RESTful API design using Swagger/OpenAPI, API security, and governance across multi-vendor integration environments.
• Defined reference architecture for complex business applications, working with client architects and vendors to integrate multiple systems using Message Oriented Middleware, Pub-Sub, and SOA patterns.
• Mentored junior developers across backend, frontend, and architecture workflows, driving adoption of high coding standards, design patterns, unit testing, and integration testing best practices.
• Deployed containerized microservices on AWS using Docker, Kubernetes, and CI/CD pipelines, ensuring secure, scalable, and compliant operations across production environments.
• Created full-stack interfaces in React + TypeScript for administration, document workflows, analytics dashboards, and user-facing interactions integrated with SQL and NoSQL data stores.

Senior Software Engineer / AI Engineer - Jaburg Wilk - Phoenix, AZ

(2023-01 - 2024-06)

• Architected and delivered a production-ready legal document automation platform powered by machine learning-driven LLMs and Retrieval-Augmented Generation (RAG).
• Built large-scale document ingestion pipelines for case files, PDFs, contracts, and long-form legal text using Python, OCR, and NLP preprocessing.
• Developed end-to-end RAG systems leveraging LangChain, LlamaIndex, FAISS/Pinecone, vector embeddings, semantic search, hybrid search, and domain-tuned retrievers.
• Designed a scalable FastAPI backend integrated with React frontend to support attorney workflows, case summaries, document classification, and entity extraction.
• Implemented evaluation frameworks using PyTorch and TensorFlow for LLM accuracy, hallucination detection, and data consistency across multiple use cases.
• Integrated model observability via LangSmith and custom logging to track performance over large datasets.

Software Engineer - Moescape AI - New York, NY

(2022-09 - 2023-05)

• Developed core infrastructure for an AI-enabled creative platform supporting anime-style image generation, avatar creation, and AI-based interactions.
• Fine-tuned advanced image generation models using PyTorch and TensorFlow, including Stable Diffusion, SDXL, Flux, ControlNet, LoRA, and DreamBooth, creating personalized style outputs for users.
• Built automated dataset preprocessing systems for image cleaning, augmentation, and metadata structuring to improve fine-tuning quality.
• Implemented high-throughput inference pipelines using Python, GPU acceleration, diffusers, and optimized model loading for low-latency generation.
• Deployed scalable workloads to AWS, Runpod, Docker, and Kubernetes, enabling cost-efficient GPU utilization.
• Built frontend features with React + TypeScript, including real-time image generation UI, companion interactions, and monitoring tools.

Backend Developer / Software Engineer - Keeper Tax Inc. - San Francisco, CA

(2020-05 - 2022-08)

• Built large-scale ETL pipelines and backend services using Python and FastAPI, implementing asynchronous processing, performance tuning, and concurrency control for high-volume document workflows processing thousands of records per hour.
• Designed and maintained RESTful API services with JWT-based authentication and role-based access control, supporting multi-format document ingestion, validation, and extraction workflows.
• Optimized SQL Server and PostgreSQL queries, stored procedures, and transaction management to ensure data consistency, minimize deadlocks, and improve data pipeline performance.
• Implemented advanced caching strategies using Redis and optimized I/O handling for high-throughput backend services.

Full-Stack & Video Streaming Developer - FreeCast Inc. - Oklahoma, OK

(2018-02 - 2020-04)

• Built and maintained a large-scale video streaming portal using Python backend services and JavaScript frontend applications.
• Implemented real-time advertisement insertion into video streams, improving monetization and viewer engagement.
• Developed an object detection pipeline using OpenCV and PyTorch-based ML models to analyze video frames and extract metadata.
• Built reinforcement-learning-driven video recommendation logic, improving content relevance and viewer retention.
• Delivered full-stack features across backend APIs, UI interfaces, database models, and performance optimization initiatives.

Bachelor of Science - Computer Science - University of California, San Diego (UCSD) (2013 - 2017)