United States
As a Software Engineer at McGraw Hill, I contribute to the development of AI-powered academic tools, including a writing and QA assistant, leveraging Python, Go, and containerized microservices deployed on AWS Kubernetes. My work emphasizes secure, scalable solutions using REST/gRPC APIs, Kafka-based event processing, and OAuth2/JWT security protocols. A graduate of the University of Tampa with a Master's in Information Technology and Management, I bring a strong foundation in software engineering and applied AI. My focus is on creating innovative, data-driven platforms to enhance efficiency and deliver impactful solutions in the education technology space.
• Developed an AI-powered academic writing/QA assistant using Python and Go microservices. • Integrated REST/gRPC APIs and Kafka-based event processing for secure student support. • Containerized services with Docker and deployed on Kubernetes in AWS, enhancing CI/CD workflows. • Leveraged OAuth2/JWT security and managed database migrations with Liquibase for scalability.
• Engineered distributed multi-agent systems using LangChain and Python to automate large-scale product analysis and vendor selection, improving task throughput and reducing decision latency. • Built asynchronous messaging pipelines with RabbitMQ, Elasticsearch-backed semantic retrieval, and PostgreSQL optimizations to support reliable, high-performance distributed workflows.
• Developed AI-enabled data platforms using Retrieval-Augmented Generation (RAG), PostgreSQL, Redis, and vector-based search to support semantic retrieval and question-answering across academic document repositories. • Worked as a team to build full-stack applications with React and Python APIs, integrating TensorFlow, PyTorch, and LLM inference services to optimize retrieval performance, and deliver real-time AI-driven responses.
• Engineered scalable Python-based distributed systems to automate enterprise document migration, enhancing efficiency. • Implemented event-driven workflows and asynchronous processing to minimize manual intervention in data handling. • Containerized and deployed cloud-native microservices using Docker and Kubernetes, ensuring high availability and fault tolerance.
• Designed and developed RESTful web services using Python frameworks, enabling secure client access. • Processed and transformed REST API responses in XML and JSON formats, integrating with frontend components. • Utilized Google Big Query Data Transfer Service for secure migration of schemas and datasets from Teradata.