Jason Guo

Senior Backend Engineer with 10 years of experience building HIPAA-compliant, cloud-native systems in healthcare and large-scale environments.

Experience delivering real-time data processing systems and LLM-powered AI platforms in production environments. Strong in Python, Go, and TypeScript/Node.js, with hands-on experience in microservices, AWS, Kubernetes, and DevOps practices. Experienced in PostgreSQL, Redis, and high-throughput data pipelines, with a focus on reliability and system design.

Senior Backend Engineer at Medely (2023-04 - Present)

• Built backend systems for Talent Fusion, a real-time healthcare staffing platform, using Python, Go, Node.js, AWS, Kubernetes, Kafka/SQS, Redis, and PostgreSQL.
• Designed and delivered an AI-driven shift-matching engine with LLM-powered feature extraction, improving match accuracy by 35% and reducing time-to-fill for urgent roles.
• Developed Go-based event workers using goroutines, channels, worker pools, and context cancellation to process high-volume staffing events reliably.
• Built Python ETL and LLM pipelines with schema validation, content hashing, caching, idempotency, and cost controls to improve feature quality and reduce duplicate LLM calls.
• Built and maintained Node.js APIs for matching, booking, notifications, and analytics dashboards, supporting real-time staffing workflows.
• Improved API performance through Redis caching, rate limiting, database indexing, and query optimization, reducing average response latency by 30%.
• Deployed services on AWS Kubernetes infrastructure using Docker, Terraform, and GitHub Actions, reducing release cycles by 50%.
• Improved production reliability with Datadog dashboards, distributed tracing, structured logging, and alerting, helping maintain 99.9%+ uptime.

Software Development Engineer III at Amazon (2019-04 - 2023-03)

• Built and scaled backend services using Django + DRF, powering real-time IoT telemetry systems.
• Engineered a high-throughput ingestion pipeline (Django, Celery, AWS IoT Core, Kinesis, Lambda) processing 50M+ events/day.
• Developed real-time dashboards with Django Channels, WebSocket, and React, reducing equipment downtime by 25%.
• Architected serverless microservices using API Gateway, DynamoDB, PostgreSQL, Step Functions, cutting infrastructure costs by 40%.
• Built data lake pipelines using Python, S3, and Athena, reducing reporting time from hours to minutes.
• Applied CQRS and modular Django app design to improve system maintainability and scalability.
• Strengthened API and platform security with OAuth, RBAC, IAM boundaries, and encryption, reducing vulnerabilities by 40%.
• Enhanced observability via CloudWatch, structured logging, custom middleware, and tracing, improving issue resolution speed by 60%.
• Co-led backend architecture reviews to ensure fault tolerance, scalability, and SLA compliance.
• Expanded automated testing (pytest, Django test framework) and CI pipelines, achieving 98%+ deployment success.

Software Engineer at Deloitte (2017-01 - 2019-03)

• Designed and built distributed microservices in Java with Spring Boot, Kafka, Redis, and Postgres serving millions of daily requests with 99.99% uptime.
• Developed Kafka producers/consumers for event-driven workflows processing high-volume streaming data with guaranteed delivery and ordering semantics.
• Architected and maintained RESTful APIs supporting real-time operations for customer-facing systems.
• Implemented performance optimizations including JVM tuning, thread pool sizing, Redis caching, and query optimization, reducing API latency by 40%.
• Deployed and operated cloud-native applications on AWS EKS, managing auto-scaling policies and rolling upgrades with zero downtime.
• Built automated testing frameworks using JUnit, TestNG, and K6, achieving 90% coverage for critical services.
• Integrated OpenTelemetry and Grafana dashboards to improve observability and reduce MTTR by 50%.
• Used AI-assisted coding tools (Claude, Copilot) to accelerate development, test generation, and code refactoring.
• Supported production incident response, leveraging Splunk for log analysis, heap dump inspection, and root-cause troubleshooting.
• Led architecture reviews and mentored junior engineers on microservices, Kafka, and cloud best practices.

Bachelor's in Computer Science - University of Texas - Austin (2012-09 - 2016-05)