Shoukath Ali

About

LLM-focused engineer who has shipped multiple production-grade AI reliability systems: an LLM output validation/monitoring service (FastAPI) with prompt versioning and failure analytics, plus a RAG feature using embeddings/vector DBs with retrieval thresholds, schema/context validation, and safe fallbacks. Strong in evaluation loops (groundedness, schema accuracy, human review) and scalable pipelines for messy document ingestion with observability and early detection of data quality issues.

Experience

Education

Key Strengths

• Shipped production LLM validation/monitoring service integrated into workflows
• Designed layered validation (rule-based + semantic) to balance strictness and flexibility
• Built production RAG pipeline (ingest/chunk/embed/store/retrieve) with guardrails to reduce hallucinations
• Implemented robust guardrails: retrieval thresholds, schema/required-field checks, context consistency, safe fallbacks
• Established LLM evaluation loop with groundedness and schema metrics plus structured human review
• Used eval results to drive prompt/validation changes and prevent regressions
• Built scalable messy-document ingestion pipeline with normalization, schema checks, retries, logging, and monitoring
• Proactively detected and fixed downstream-breaking data issues via observability and validation