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Jiacheng Yin
Intern software engineer specializing in AI, backend systems, and cloud infrastructure
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Backend/AI systems engineer who has shipped production LLM agents focused on prompt engineering, code generation, and incident-response automation. Stands out for combining strong agent orchestration and reliability engineering with measurable business impact, including 60-70% cost reductions, 45% lower monthly LLM spend, and a 5x increase in developer iteration speed.
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Key Strengths
- Built production LLM agents with reliability, cost control, and versioning focus
- Architected multi-step agent workflows end-to-end
- Strong production hardening for AI systems
- Designed fallback and rollback mechanisms using provider switching and hashed state
- Reduced redundant LLM costs by 60-70%
- Lowered monthly LLM costs by 45%
- Improved developer throughput from 2-3 to 10-12 prompt iterations per day
- Enabled 30% faster time to market for AI features
- Designed evaluation and monitoring loops for agent reliability
- Improved agent reliability through targeted error analysis of API parsing failures
- Handled messy operational/security data with normalization, validation, and idempotency controls
- Prevented bad downstream actions using quarantine queues and circuit breakers
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