I'm a Senior AI/ML Engineer at Quantiphi with 4+ years of experience building and shipping production-grade AI systems, currently focused on agentic AI and Generative AI applications on AWS.
At Quantiphi, I've worked across the full lifecycle of AI systems — from architecture to production deployment to measuring real business impact. A few things I'm proud of:
I architected an LLM-powered document intelligence pipeline on AWS (Lambda, Textract, Bedrock Claude, S3, DynamoDB) that extracts structured data from multilingual student transcripts, cutting turnaround time by over 80% and eliminating $200 in per-student evaluation cost.
I designed a multi-agent LLM orchestration workflow using LangGraph — with parallel execution and tool-calling — to extract and validate entities from semi-structured invoices, reducing manual review effort by roughly 60%.
I shipped an end-to-end RAG system for a pharma client and built an RLHF fine-tuning pipeline for LLaMA 3.1 using PEFT/LoRA and quantization.
I have implemented an LLM-as-a-judge evaluation layer to automatically score and monitor production LLM outputs — because I think evaluation and observability are as important as the model itself once something is in production.
I've also worked on regulated, compliance-sensitive systems: a dental claims extraction pipeline (LayoutLM + YOLOv8) that reduced processing time by 70%, with automated PII redaction built into the pipeline.
Outside of client work, I build agentic and multimodal systems on my own time — a multi-hop Agentic RAG chatbot combining FAISS and GraphRAG for knowledge-graph retrieval, extended to handle audio and video via Whisper, AWS Transcribe, and CLIP embeddings, and a CrewAI-based multi-agent system for automated data analysis.
My technical interests center on agentic AI systems — how agents reason, plan, use tools, and maintain memory over long-running tasks — along with LLM evaluation and observability, and RAG/retrieval architecture. I hold AWS Certified Solutions Architect – Associate and AWS Certified Machine Learning – Specialty certifications.
I'm looking to move into roles with deeper ownership of agent architecture — systems where I'm making the core design decisions on reasoning, memory, and reliability, rather than primarily building on top of existing frameworks — ideally in high-stakes or regulated domains where explainability and auditability matter.
