Computer Science graduate from the University of Arizona (3.85 GPA, Dean's List) with a focus on AI systems, backend engineering, and distributed systems. I build production-grade systems at the intersection of language models and real infrastructure — from RAG pipelines and LLM evaluation to distributed key-value stores, OS-level C work, and full-stack AI platforms.
AI Systems Engineer POC
University of Arizona × McGraw Hill · Remote
- Built production backend for a RAG-based AI assistant: document ingestion, retrieval pipeline, prompt routing, and GPT API integration.
- Designed role-based access controls and retrieval scoping enabling instructors to configure assistants constrained to course materials.
- Iterated on chunking and retrieval strategies to improve multi-step query accuracy and output consistency across configurations.
- Developed test harnesses to validate retrieval quality and output behavior across model and configuration changes.
Computer Science Fellow
Handshake AI MOVE Program · Remote
- Built reproducible Docker CI environments for automated testing of AI agent patches across diverse codebases at scale.
- Re-implemented bug fixes across unfamiliar codebases as ground-truth; authored fail-to-pass test suites enabling automated patch validation.
- Designed structured test harness patterns to improve coverage and reproducibility across agent-generated software patches.
- Collaborated with engineering leads to refine prompt patterns and structured output formats, improving signal quality across benchmark iterations.
Founding Engineer
SkillfullyAware (SAAQ) App · Tucson
- Designed and built scalable REST API services processing structured and unstructured user input into analytics and reporting pipelines.
- Led MVP backend from scratch: data models, service architecture, LLM API integrations, and vector retrieval shipped under fast-moving requirements.
- Delivered features end-to-end across API, data layer, and system integrations; defined architecture patterns for extensible development.
AI Solutions Developer
Andrew Weil Center for Integrative Medicine · Tucson
- Built modular backend services and document ingestion pipelines for AI-driven healthcare applications emphasizing fault tolerance.
- Integrated AWS components (Lambda, S3) to support backend workflows; standardized API contracts and schemas across ingestion pipelines.
- Collaborated with clinical and technical teams to define reliability requirements for services handling structured medical content.
GRC Business Analyst
University of Arizona ITS · Tucson
- Automated compliance workflows with scripting and data pipelines, reducing manual effort and risk across recurring audit processes.
- Built reporting dashboards for audit-ready enterprise systems serving large cross-functional stakeholder groups at scale.
- Partnered with compliance officers & system owners using ServiceNow GRC to assess controls and drive timely remediation.
- Standardized data tracking and reporting across teams, improving compliance visibility and reducing audit cycle overhead.
Full-stack web platform with a TypeScript/Next.js frontend, REST API backend, Prisma ORM with Neon Postgres, and a modular test execution engine — ships risk-tiered verdicts and structured reports exportable as JSON/CSV, deployed on Vercel.
Distributed key-value store with Raft consensus for leader election and log replication — achieves linearizable reads and fault-tolerant writes validated under simulated node failures and network partitions.
Cooperative coroutine (fiber) library in C — hand-written x86-64 context switch, FIFO scheduler, and co_yield / co_await primitives. Zero dependencies.
POSIX-compliant Unix shell written in C — supports pipes, I/O redirection, job control, signal handling, and built-in commands.
- Building production-quality distributed systems and backend infrastructure in Go and C
- LLM reliability, RAG evaluation, and reducing hallucination in production AI pipelines
- Scalable backend architecture, consensus algorithms, and systems design at scale
When I'm not building or coding, I like pushing myself in other ways, whether through training, sports, or learning about geopolitics and human behavior. I'm naturally curious about how complex systems work, and that perspective shows up in the way I think about software and real-world problems.