I am a Staff Software Engineer with over 10 years of experience leading the design and delivery of large-scale systems in Healthtech, Fintech, and E-Commerce sectors. Throughout my career, I have specialized in scaling distributed platforms, driving architectural modernization, and mentoring engineering teams to achieve high performance and reliability. I am passionate about delivering resilient, secure, and user-centric solutions that support millions of users and mission-critical operations.
My expertise spans multiple programming languages including Java, Python, Scala, JavaScript/TypeScript, Ruby, Go, and C#. I have extensive experience working with modern technologies such as Spring Boot, J2EE, Django, Flask, Node.js, React, Kubernetes, AWS, Azure, and GCP. I am skilled in building microservices architectures, deploying machine learning models in production, and optimizing system scalability and performance.
At Teladoc Health, I have been instrumental in creating and scaling polyglot microservices that power AI transcription, referrals, and care delivery for millions of members. I have deployed predictive ML models that significantly improved patient engagement and health outcomes. My work involves building real-time data pipelines and leveraging cloud platforms to enhance clinician workflows.
Previously, at PayPal, I developed a fraud detection engine that reduced fraudulent transactions by 35% and designed RESTful APIs to support over 10 million daily transactions. I also enhanced front-end applications to improve user experience and checkout completion rates. At eBay, I engineered AI-powered services and modernized API platforms to support billions in gross merchandise volume.
I am committed to continuous learning and applying best practices in software engineering, agile methodologies, and cross-functional collaboration. I enjoy mentoring colleagues and driving technical leadership to deliver impactful solutions. I am eager to contribute my skills and experience to innovative projects that improve user experiences and operational efficiency.
Created and scaled polyglot microservices (Java, Node.js, Ruby, React) for high-availability SaaS, powering AI transcription, referrals, and care delivery across thousands of clients and 93 million members. Established hybrid Java/Spring Boot and Python services powering AI platforms, enabling clinicians to monitor 25% more patients with real-time edge processing. Deployed predictive ML models (TensorFlow, PyTorch) in production pipelines, achieving 3× engagement and 0.4% A1c reduction in chronic care outcomes. Built real-time data pipelines on AWS/Azure with Kafka, APIs, and distributed databases, boosting clinician referrals by 40% year-over-year.
Built a fraud detection engine using Java and Spring Boot, integrating with Node.js for real-time transaction analysis, reducing fraudulent transactions by 35%. Designed RESTful APIs with J2EE and Hibernate to process payment data, improving API response time by 40% and supporting 10M+ daily transactions. Enhanced front-end applications with React and TypeScript, streamlining user workflows and increasing checkout completion rates by 20%.
Engineered an AI ShopBot using Java/Scala/Python, GCP, BigTable, and Spark microservices, improving multi-modal query relevance by 30%. Architected a parallel bidding exchange with Java, Docker, and real-time messaging, reducing page load by 60% and boosting ad yield. Modernized the API platform from SOAP to REST/JSON, OAuth2, JVM/Node.js, enabling $5B GMV through new integrations.
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