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Rafael Martinez
Director-level Applied AI & Data Analytics Engineer specializing in real-time decisioning systems
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About
Built and shipped a production AI/LLM agent-based, event-driven credit underwriting/decisioning workflow that automated document understanding, retrieval, risk scoring, and compliance checks—cutting turnaround from ~90 days to ~5 minutes while boosting throughput 200x+ and approvals ~50%. Experienced with Airflow/Prefect orchestration, Redis/RabbitMQ queues, rigorous eval/monitoring, and close collaboration with non-technical underwriting teams.
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Key Strengths
- Built and deployed a real-time AI-driven credit decisioning system replacing a ~90-day manual process
- End-to-end orchestration of multi-component pipelines (parsing, retrieval, LLM structuring, ML scoring, compliance checks)
- Designed event-driven Python architecture with queues to achieve deterministic latency in production
- Delivered major business impact: reduced decision time to ~5 minutes, increased throughput 200x+, improved approvals by ~50%
- Strong evaluation and reliability practices: modular validations, prompt/function unit tests, static test sets, automated evals, production monitoring and safety gates
- Effective cross-functional communication with non-technical underwriting stakeholders using visual prototypes and real examples
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