Steven Chen

Full Stack Software Engineer and Salesforce Application/Integration Architect with 10+ years delivering scalable backend and frontend solutions across healthcare, financial services, and retail SaaS. Salesforce experience since 2019, including Apex, Lightning Components/LWC, Visualforce Pages, Flows, SOQL/SOSL, API integrations, security model design, and CRM workflow delivery. Backend expertise includes Python, Rust, Go, Node.js, microservices, REST/GraphQL APIs, event-driven architecture, and cloud-native systems.

Spearheaded systems processing over $840M in financial transactions and optimized healthcare workflows impacting millions of clinical events daily, driving 34% faster loan approvals and 17% lower clinical system latency.

Lead Architect / Senior Software Engineer at NYU Langone Health (2021-09 – Present)

• Led Salesforce delivery for healthcare workflow initiatives, aligning CRM data models, case/task routing, and provider-facing operational workflows with HIPAA-compliant clinical platforms.
• Built and enhanced Apex services, Lightning Components/LWC, Visualforce Pages, Flows, and REST integrations supporting care coordination, clinical operations dashboards, and secure user workflows.
• Engineered Python and Go-based HIPAA-compliant microservices supporting clinical workflows, increasing throughput of patient data exchanges by 22% while reducing latency by 17% during peak usage.
• Implemented secure role-based access controls, Salesforce permission patterns, and audit logging, decreasing PHI exposure incidents by 15% and enhancing compliance with healthcare regulations.
• Collaborated with clinical informatics and product teams to develop FHIR API integrations facilitating interoperability with Epic and Cerner EHR systems, improving care coordination efficiency by 18%.
• Optimized SQL Server database queries and introduced caching layers that accelerated clinical decision support response times by 16%, enhancing provider workflow productivity.

Senior Software Engineer at American Express (2019-07 – 2021-08)

• Developed Salesforce CRM integrations and Lightning-based workflow components supporting lending, underwriting, and customer operations, improving visibility into approval and document review processes.
• Architected and delivered a React/Redux frontend coupled with Python and Node.js microservices for a mortgage underwriting platform handling $840M in loan volume, reducing approval cycles by 34%.
• Devised Python automation services with AWS Step Functions and Lambda orchestrations to automate 17 underwriting processes, cutting manual processing by 63 hours weekly and boosting data accuracy by 28%.
• Developed AI-powered document classification pipelines using AWS SageMaker and S3, achieving 91% classification accuracy and halving manual review times.
• Implemented GraphQL APIs and Python/Go RESTful services across 14 backend microservices, improving cross-team integration velocity by 41% and decreasing average API latency from 890ms to 340ms.
• Streamlined CI/CD pipelines with AWS CodePipeline and ECS Fargate, accelerating deployment frequency threefold while maintaining rigorous PCI DSS security standards.

Full Stack Web Developer / Salesforce Developer at Revolent Group (2014-10 – 2019-06)

• Developed Salesforce customizations using Apex, Visualforce Pages, Lightning Components, Flows, and SOQL for retail/POS workflows including inventory, orders, cashier checkout, reporting, chat, and task management.
• Developed a fintech payment platform using Go, Rust, Node.js, React, and TypeScript incorporating AI-driven payment routing algorithms, reducing transaction latency by 43% across 127,000 monthly blockchain transactions.
• Integrated OpenAI and Claude LLM APIs with DynamoDB vector stores to enhance fraud detection workflows, lowering false positive rates by 33% while sustaining 99.7% system availability.
• Designed event-driven architectures using Go services, AWS Lambda, and Step Functions for distributed payment processing, cutting operational overhead by 38% and enabling real-time transaction monitoring.
• Established automated CI/CD pipelines via GitHub Actions and AWS ECS supporting SOC 2 compliant deployments, shrinking release cycles from six weeks to nine days.
• Built MLOps observability dashboards with AWS CloudWatch for AI model performance, facilitating delivery of 22 AI-enhanced features with 97% uptime and reliability.

Bachelor's Degree – University of California, Berkeley (2014-05)