MS Information Systems · Northeastern University
I build production-grade AI systems — RAG pipelines, autonomous agent frameworks, and scalable backend infrastructure. Focused on making LLM applications reliable and deployable in the real world.
Open to Open to AI Infra / LLMOps / AI Backend Engineering roles roles
AI & LLM Systems
Backend
Frontend
Cloud & DevOps
| Metric | Result |
|---|---|
| Embedding API cost reduction | 93% (30 → 2 calls/doc via batching + SHA-256 dedup) |
| RAG throughput | ~41 req/min, P95 6.1s, 0% error (JMeter) |
| RAGAS answer relevancy | 0.952 |
| LLM eval platform throughput | 4,800+ req/sec, P99 328ms |
| Redis cache latency | 1,962ms → 0ms on cache hits |
Autonomous AI agent system integrating RAG pipelines with tool-calling agents.
- Hybrid retrieval: vector search (PGVector HNSW) + BM25 via RRF fusion, cross-encoder reranking (ms-marco-MiniLM-L-6-v2) via Python FastAPI
- ReAct hierarchical agent:
BaseAgent → ReActAgent → ToolCallAgent → LingManuswith stuck-state detection and human-in-the-loop escalation - 8 tool callbacks + custom MCP Server (Pexels image search, Stdio/SSE transport) + Amap location MCP integration
- LangSmith tracing via OpenTelemetry · SSE streaming · CI/CD with Docker Buildx ARM→amd64
Spring Boot Spring AI PGVector Python FastAPI Vue 3 AWS EC2 LangSmith
Full-stack clinic platform with a RAG-based AI health assistant grounded in an internal medical knowledge base.
- RAG pipeline: PDF ingestion → SHA-256 dedup → chunking → OpenAI embedding → PGVector (HNSW) → hybrid retrieval → RRF → SSE streaming
- RAGAS evaluation: Faithfulness 0.896 · Answer Relevancy 0.952 · Latency 310ms
- Patient booking system + admin document upload pipeline + knowledge base management
Spring Boot Vue 3 PostgreSQL PGVector OpenAI AWS EC2 Nginx
Distributed system for benchmarking LLM reliability, latency, and output quality.
- Kafka-based async pipeline decoupling model inference (2–37s) from API responses
- Redis Lua atomic caching: latency 1,962ms → 0ms on cache hits
- Sustained 4,800+ req/sec, P99 328ms · retry strategies + dead-letter queues
- Elasticsearch prompt search · Prometheus + Grafana observability
Spring Boot Apache Kafka Redis CockroachDB Prometheus Grafana React
Distributed gateway handling authentication, routing, and traffic control across 20+ backend services.
- Redis-based rate limiting and circuit breaker · AK/SK signature authentication · Dubbo RPC integration
Spring Boot Redis Dubbo
Natural language prompts → deployable web applications.
- Diagnosed concurrency bottleneck in SSE parsing · parallel streaming execution reduced latency by 28%
Spring Boot SSE
- LinkedIn: duan-ling-9970ba350
- Email: duan.lin@northeastern.edu