From medical diagnostics to production clinical AI.

Zasti Inc, the University of Cincinnati, and Technocolabs Softwares — clinical AI, higher education, and medical diagnostics.

1. May 2024 — Present

   Zasti Inc — AI Engineer

   Ashburn, VA · Healthcare / clinical AI

   • Architected a production RAPTOR RAG system with hierarchical summarization, Neo4j knowledge-graph integration, and dual-stage vector retrieval (FAISS + Pinecone): 45% faster queries, 38% better factual accuracy, 50M+ document embeddings at sub-100ms P99 latency.
   • Built a shared agent harness (LangGraph through MCP) and four automation pipelines on it — sales, resource tracking, marketing, and internal software-engineering agents — adopted company-wide including leadership, with human approval gates before any consequential action.
   • Designed a multi-agent orchestration platform (LangGraph, LlamaIndex) with autonomous task planning, tool use, self-reflection loops, and short/long-term memory — automating 95% of clinical research workflows; manual review cycles cut from 3 days to under 4 hours.
   • Diagnosed and fixed non-convergent agent loops by restructuring work as an explicit task-dependency map with single-task execution rather than whole-goal reasoning, and layered validation gates that caught hallucinated agent output before it reached a human reviewer.
   • Engineered a multimodal RAG pipeline (GPT-4V vision, custom OCR post-processors, FHIR-compliant parsers) with hallucination detection via chain-of-thought consistency scoring: 92% retrieval precision across 15+ heterogeneous lab-report formats.
   • Cut LLM inference costs 75% (~$2K/month) via GPTQ 4-bit quantization, speculative decoding, and dynamic batching with vLLM — 98% performance parity on clinical benchmarks (MIRAGE, MedQA).
   • Established AI governance and safety guardrails (RAGAS, LangSmith): 62% lower production hallucination rate, HIPAA-aligned audit logging for all clinical AI outputs.

2. Aug 2022 — Apr 2024

   University of Cincinnati — Graduate Teaching Assistant

   Cincinnati, OH · Higher education

   • Designed and delivered hands-on workshops in Python, cloud computing, and ML for 500+ graduate students; 90% assignment completion, 95% positive feedback.
   • Mentored 20+ graduate students on capstone research (NLP, CV, predictive analytics); 4 projects selected for departmental showcase, 2 led to published conference abstracts.
   • Built scalable educational resources with responsible-AI principles alongside faculty; +40% engagement, −25% time-to-completion on advanced ML assignments.

3. Feb 2021 — Jul 2022

   Technocolabs Softwares — Deep Learning Developer

   Remote · Medical diagnostics

   • Led a 4-member team building deep-learning models for a medical-diagnostics product (PyTorch CNNs, ResNet/EfficientNet transfer learning): 88% diagnostic accuracy on held-out clinical test sets, 45% higher system efficiency.
   • Designed a pattern-recognition algorithm combining attention-based feature extraction with ensemble classification: +25% predictive accuracy over baseline for clinical decision support.
   • Built Power BI dashboards with real-time model tracking and SHAP explainability, contributing to a 10% diagnostic-accuracy improvement.