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Daniel Panrong Dai
Junior Software Engineer specializing in AI and full-stack development
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About
Consulting-background AI practitioner who led a production LLM pipeline on Snowflake Cortex to map hundreds of thousands of messy OCR/form-based contract fields into standardized Salesforce fields, including confidence scoring and an LLM-driven feedback loop. Strong focus on real-world constraints—token limits, cost control, and evaluation without ground truth—paired with frequent stakeholder-facing progress reporting.
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Key Strengths
- Led production deployment of an LLM system to map large volumes of heterogeneous contract forms to standardized Salesforce fields
- Deep practical understanding of LLM token limits, cost tradeoffs, and context-window performance issues (e.g., needle-in-haystack failure modes)
- Strong at reducing problem scope via data engineering and constrained/structured outputs to improve accuracy and control cost
- Builds evaluation approaches when ground truth is missing using stakeholder/user review and measurable human feedback loops
- Experienced consulting-style communication with non-technical stakeholders; manages expectations by clearly explaining AI limitations and tradeoffs
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