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Shiva Dasi
Mid-level Software Engineer specializing in LLM agents and cloud-native systems
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About
Built and shipped production LLM agents in compliance-sensitive environments (FERPA), emphasizing reliability via structured outputs, state-graph orchestration (LangGraph), and CI-driven eval/regression testing. Also has experience hardening messy ERP ingestion pipelines at scale (50K monthly orders) with normalization, idempotency/deduplication, and robust failure handling using AWS (SQS/CloudWatch) and PostgreSQL.
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Key Strengths
- Shipped FERPA-compliant LLM agent to production with reliability-first design
- Built layered monitoring with schema validation, confidence thresholds, and fallback routing to prevent silent failures
- Implemented CI-based agent regression evals (GitHub Actions) targeting specific failure modes
- Designed multi-step agent orchestration via explicit state graph (LangGraph) with constrained tool access
- Improved accuracy from ~88% to ~94% through error analysis and retrieval strategy fallback for sparse histories
- Selective memory/retrieval design combining embeddings + rule-based filters; validated via ablation testing
- Stabilized messy ERP ingestion at scale (50K monthly orders) using canonical schemas, deduplication hashes, DLQ, and loud failure logging
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