Flew 8,000 miles to make lattes and build multi agent workflows, knowledge graphs, and whatever dropped on Hacker News this morning. The latency on my job offers is higher than my p99. Still deploying.
What separates you from the AI you're building? Student loans.
MS Computer Science @ University of Colorado Boulder (GPA 3.9) - Aug-2024 - May 2026.
I build backend systems, distributed AI pipelines, and multi-agent applications.
Previously at the BioFrontiers Institute (Peleg Lab) where I worked on distributed GPU training infrastructure on GCP.
Currently building a multi-agent relationship intelligence platform using LangGraph, RAG, and knowledge graphs.
Graduate Researcher - Peleg Lab, BioFrontiers Institute Aug 2025 – Jan 2026
Parallel AI pipelines in Python/C++ on GCP. 35% throughput improvement, 40% faster fault diagnosis via GDB/Valgrind profiling.
Graduate Teaching Assistant - Lab Systems, CU Boulder Jan 2026 – May 2026
Led 3 lab sections (55+ students). Workflow analysis in R to identify bottlenecks in lab operations.
Software Engineering Intern - CodeClause Jun 2024 – Jul 2024
Flask REST APIs, Jenkins CI/CD pipelines, structured logging and observability. 20% backend throughput increase.
Software Engineer Intern - Adflix Media Apr 2023 – Sep 2023
SQL ETL pipelines processing 5M+ records/day. Grafana monitoring dashboards, Dockerized microservices.
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Kith(Multi-Agent Relationship Intelligence Platform) Extracts and maps contacts from emails, docs, and meeting notes into a live knowledge graph of 1,000+ entities. 80% less manual networking effort.
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Distributed debugging platform localizing flaky tests across 100K+ LOC repos via graph-based code analysis. 70–85% less inter-service data transfer.
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Backend data platform processing 17M+ records. Versioned microservices, Dockerized CI/CD, 30% fewer validation errors.
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Streaming ML pipeline processing live event data and exposing anomaly predictions through backend APIs in real time.
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Peleg Lab - GPU Infrastructure Parallel AI pipelines on GCP for distributed ML. 35% throughput gain, 40% faster fault diagnosis via GDB/Valgrind.
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TripSync – AI Multi-Agent Travel Planning System Multi-agent trip planner aggregating group preferences and generating optimized itineraries using LLM orchestration.
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Languages - Python, JavaScript, TypeScript, Go, Java, C++, SQL
AI Engineering - LangChain, LangGraph, RAG Pipelines, Multi-Agent Workflows, Vector Search, Embeddings, Context Engineering, LLM Evaluation, Fine-Tuning, AI Observability, Token Optimization, Multimodal AI
Backend & Systems - FastAPI, Node.js, Express.js, REST APIs, Microservices, Distributed Systems, Async & Event-Driven Architectures, JWT, OAuth 2.0, RBAC, Linux
Databases & Data - PostgreSQL, MongoDB, Redis, DynamoDB, Qdrant, ETL Pipelines, Query Optimization
Cloud & DevOps - AWS (EC2, S3, ECS, IAM), GCP, Docker, Kubernetes, Terraform, CI/CD, GitHub Actions, Nginx
Networking & Security - DNS, HTTP/HTTPS, TCP/IP, TLS/SSL, Load Balancing, CDN, Reverse Proxies, Secure API Design, OWASP Fundamentals, Rate Limiting
Testing & Observability - OpenTelemetry, Grafana, Structured Logging, Pytest, Jest, Playwright, Unit, Integration & E2E Testing