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Yash Jajoo
Senior Software Engineer specializing in AI and FinTech platforms
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Built a production LLM pipeline at Walter AI that scans massive user inboxes, identifies financial newsletters, and extracts trading strategies into structured JSON for downstream paper-trading workflows. Stands out for combining agent architecture with strong production discipline—cutting scan time from 20 to 5 minutes, reducing LLM costs by 90%, and achieving 3-second P99 latency while handling messy, inconsistent email data at scale.
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Key Strengths
- shipped a production LLM agent for financial newsletter extraction
- optimized large-scale inbox processing for 100k+ emails
- reduced scan time from 20 minutes to 5 minutes
- achieved 90% LLM cost reduction
- delivered P99 end-to-end latency of 3 seconds
- designed multi-step pipelines with strict schema interfaces
- built resilient orchestration with checkpointing and resumable state
- improved reliability through strict JSON validation and retries
- created offline eval datasets from real production data
- implemented idempotency and edge-case isolation for messy email data
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