# Danling Wei

> AI Infra & Backend Engineer | LLM, Elasticsearch, Data Pipelines

Location: New York, New York, United States
Profile: https://flows.cv/danlingwei

I’m a software engineer focused on AI infrastructure, backend systems, and scalable data platforms.

At PiSrc, I’ve worked on production AI and search systems including an AI skills orchestrator for agentic authoring and QA, an enterprise RAG platform for customer support, large-scale product data ingestion pipelines, and Elasticsearch-based search experiences. My work has focused on building reliable, fault-tolerant systems that improve automation, search quality, and operational efficiency.

I’m especially interested in LLM applications, retrieval systems, distributed backend architecture, and data-intensive products. I enjoy turning ambiguous product needs into production-ready systems with clear engineering tradeoffs and measurable business impact.

Core areas: Python, Java, TypeScript, LLM integration, RAG, Elasticsearch, Redis, Weaviate, FastAPI, Spring Boot, Docker, and cloud-based deployment.

## Work Experience
### Full Stack Developer @ PiSrc
Jan 2024 – Present | New York, New York, United States
• Architected and implemented an AI Skills Orchestrator powering agentic authoring and QA workflows, reducing content authoring time by 60%+ through automated drafting and validation.

• Built and deployed an enterprise-scale RAG platform for global customer support, designing retrieval architecture with Weaviate, Redis, Haystack, and reranking to improve resolution efficiency by ~60% and reduce support costs.

• Owned a large-scale product data integration pipeline processing 500K+ product records and 100K+ daily deltas across four APIs into Elasticsearch, improving consistency, tripling query performance, and reducing manual operations by ~40%.

• Led migration of a global partner locator from Lucidworks to Elasticsearch, redesigning indexing strategy and integrating Azure Maps for geospatial recommendations, cutting latency by over 50%.

• Co-developed a behavior-driven recommendation module in Adobe Experience Manager (AEM), improving CTR by ~40% and increasing engagement across technical documentation and solution pages.

• Productionized backend systems with fault-tolerant patterns including retries, fallbacks, observability, schema evolution, and idempotent ETL workflows.


## Education
### Master of Science - MS in Electrical Engineering
Columbia Engineering

### Bachelor of Engineering - BE in Software Engineering
Beijing University of Technology

### Bachelor of Science - BS in Software Engineering
University College Dublin


## Contact & Social
- LinkedIn: https://linkedin.com/in/danling-wei

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Source: https://flows.cv/danlingwei
JSON Resume: https://flows.cv/danlingwei/resume.json
Last updated: 2026-04-05