Daniel Zhang

I’m a Senior Software Engineer with 10+ years across fintech and enterprise SaaS, focused on full-stack delivery and event-driven distributed systems. At Zendesk, I architected core components of an AI-powered Resolution Platform, integrating Intelligent Triage, Omnichannel Routing, and a cost-optimized LLM Proxy to ship end-to-end capabilities for high-scale support workflows.

I build performant, reliable pipelines and AI integrations—like a real-time ticket classification pipeline using Python, FastAPI, and Apache Kafka, with inference via AWS Lambda. I also reduced AI infrastructure costs by 30% (saving an estimated $200,000 annually) by routing requests through the most cost-effective model, and improved customer outcomes with skill-based ticket matching (1M+ daily tickets in under 200ms) and RAG automation that lowered hallucinations from 12% to under 3%.

I care deeply about operational excellence and engineering productivity: I implemented observability with Datadog and OpenTelemetry to achieve 99.95% uptime for platform-critical APIs, modernized CI/CD from shell scripts to GitHub Actions with Docker and Kubernetes, and boosted platform iteration speed. Across product and ML collaboration, I also established an internal MCP server to help AI tools dynamically access internal docs and APIs—and I’ve mentored engineers on microservices, AI integration patterns, and distributed systems design.