Co-creator of Retriever (<a href="https://runretriever.app/" rel="nofollow">https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.
Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.
zanedev28 · · focus · HN ↗
Remote: Yes
Willing to relocate: Yes
Technologies: Ruby, Python, JavaScript (ES6), TypeScript, React, Node.js, PostgreSQL, MongoDB, OpenSearch/Elasticsearch, AWS (ECS, EC2, VPC, ALB, Secrets Manager), Docker, Terraform, OpenTelemetry, Jaeger, Prometheus
Resume/CV:<a href="https://drive.google.com/file/d/1aBYTxqlWIKmm59UT5ffK493tKR0" rel="nofollow">https://drive.google.com/file/d/1aBYTxqlWIKmm59UT5ffK493tKR0...
LinkedIn: <a href="https://www.linkedin.com/in/zane-lee-14496a297/" rel="nofollow">https://www.linkedin.com/in/zane-lee-14496a297/
Email: zanedev28@gmail.com
GitHub: <a href="https://github.com/Kcstills17" rel="nofollow">https://github.com/Kcstills17
Co-creator of Retriever (<a href="https://runretriever.app/" rel="nofollow">https://runretriever.app/), an AWS-deployed observability platform that enables AI-powered trace analysis through distributed systems. Built a custom MCP server allowing developers to query trace data using natural language through LLMs like Claude, optimizing context consumption through intelligent data distillation from verbose OTLP structures.
Experienced with building full-stack applications. I am comfortable using AWS as a cloud environment and have experience with AI technologies such as RAG, MCP, and Vector embeddings.