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Daming Jiang
Intern Software/AI Engineer specializing in LLM fine-tuning and agentic RAG systems
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About
Built and shipped an end-to-end LLM agent during an AT&T internship to automate network troubleshooting, with production-style reliability safeguards (timeouts/retries/fallbacks) and structured, state-machine orchestration; project won 3rd place in AT&T’s nationwide intern innovation challenge and was demoed to leadership. Also handled messy multi-partner data at Tencent by implementing schema validation/normalization, confidence-threshold fallbacks, and idempotent Python/ORM-based pipelines.
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Key Strengths
- Shipped end-to-end LLM agent automating network troubleshooting workflow
- Designed production safeguards (retries, timeouts, fallback logic) to prevent misleading/broken outputs
- Predictable agent design using explicit tool-calling control and state-machine orchestration
- Built multi-layer testing strategy (unit, integration, output accuracy) using real tickets
- Improved retrieval relevance via query rewriting iteration
- Handled messy partner/customer data with validation/normalization layers and idempotent pipelines
- AT&T nationwide intern innovation challenge: 3rd place; demoed to leadership at headquarters
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