AI/Agentic System → Cursor for Legal Discovery

• Built a multi-step reasoning engine that breaks down complex legal research questions, executes them across document collections, and synthesizes coherent answers - handles questions that would take paralegals hours or days

• Built document understanding that works across formats lawyers use - PDFs, Office docs, emails, images, audio, video

• Built multi-provider LLM abstraction with intelligent caching that cut API costs by 85%+

• Built Graph RAG that understands relationships between people, organizations, and events - finds connections keyword search misses

• Built context management that handles arbitrarily large document sets - compresses intelligently and maintains accuracy even when source material far exceeds context windows

• Built citation and provenance tracking - every AI answer links back to exact source documents with page numbers

• Zero customer complaints on answer accuracy

Knowledge Graph & Entity Resolution

• Built proprietary canonical entity resolution that disambiguates and links entities across millions of documents - connects aliases, name variations, and references scattered across thousands of pages into a unified identity graph

Infrastructure

• Designed and built the entire AWS infrastructure in Terraform - one command spins up the full stack from scratch

• Built video/audio processing with GPU-optimized clusters - handles conversion, storage optimization, and browser-playable formats at scale

• Built a custom ECS autoscaler that watches queue depth and scales workers based on queue pressure

• Set up all monitoring, CI/CD, and service-to-service communication

• Performed 95% of all SOC II and ISO 27001 compliance work - policies, controls, audit prep

Cost Engineering

• Analyzed and neutralized spend across MongoDB Atlas, AWS, and LLM API calls, saved $100,000+ in wasted infra costs

Individual contributions directly account for $100,000,000+ per quarter in ads revenue

Design and implementation of low latency systems to preserve the integrity of the user’s experience on Spotify

Lead engineer on Apple’s SkAdNetwork endpoint. Used to give Spotify credit for app installs via ads served through Spotify iOS app

Expert in root cause analysis and debugging distributed systems

Design and implementation of management, automation, data collection, performance analysis, monitoring, alerting, and root cause analysis tools

Contributions improved performance, reliability, and cost-savings, throughput for Timeline, Instagram, Oculus data pipelines

Analyzed and improved efficiency, scalability, and stability of various system resources

Scaled monitored entities by greater than 10x through design and implementation of a dependency graph

Design, coding, and testing of critical market and trading components

Wrote multi-threaded, low latency trading systems used in high frequency trading, in C++