Computer Science senior at the University of Arizona (3.85 GPA, Dean's List) with a focus on AI systems and software engineering. I build things at the intersection of language models and real products, from RAG-based GPT frameworks and LLM evaluation pipelines to founding backend systems for early-stage startups. Currently engineering AI infrastructure at UA × McGraw Hill while completing my degree in May 2026.
AI Systems Engineer POC
University of Arizona × McGraw Hill · Remote
- Architecting a controlled, RAG-based GPT framework enabling instructors to create textbook-grounded, task-specific AI assistants.
- Enforcing role-based and content-level guardrails to constrain retrieval and model behavior to approved instructional materials.
- Designing source-aware response patterns that reference specific textbook chapters or sections to improve transparency and trust.
- Optimizing retrieval design, chunking strategies, and evaluation criteria to improve response consistency and reduce hallucination risk.
CS Fellow – AI Evaluation & Prompt Engineering
Handshake AI · Remote
- Evaluated and scored 100+ AI-generated outputs weekly to benchmark instruction-following accuracy and reliability.
- Designed domain-specific prompts for LLMs, improving consistency and precision across multimodal responses.
- Provided structured feedback to strengthen AI training pipelines and documentation for research validation.
- Collaborated asynchronously in remote sprints, applying QA and version control practices to milestone-based work.
Founding Engineer
SkillfullyAware (SAAQ) App · Tucson
- Designed scalable, API-driven backend services to process structured and unstructured user input into analytics pipelines.
- Implemented RESTful services powering frontend features and internal system integrations.
- Led MVP backend development across core services, data models, and application workflows under evolving product requirements.
- Integrated external LLM APIs and vector-based retrieval components to support early-stage AI feature experimentation.
AI Solutions Developer – RAG Systems
Andrew Weil Center for Integrative Medicine · Tucson
- Built an AI-powered RAG chatbot for the CanHeal Cancer Toolkit, deployed on AWS microservices to streamline oncology resource access.
- Conducted user research and iterative testing with medical stakeholders to ensure usability and HIPAA compliance.
- Produced technical documentation and delivered client-ready demos for faculty and sponsors.
GRC Automation Analyst
University of Arizona IT Services · Tucson
- Automated ServiceNow GRC workflows, cutting manual review time by 25% and improving policy audit traceability.
- Developed SQL/PostgreSQL dashboards tracking compliance risk metrics used by three internal teams.
- Delivered Agile-based feature updates under tight deadlines while maintaining Git version control integrity.
Fault-tolerant distributed key-value store built from scratch in Go using the Raft consensus algorithm — implements leader election, log replication, snapshotting, and membership changes. Serves ~12k write ops/sec and ~18k linearizable reads/sec on a 3-node cluster via a gRPC transport layer and clean HTTP API.
POSIX-compliant Unix shell implemented from scratch in C — supports arbitrary pipeline chains, I/O redirection, background jobs, signal handling (SIGINT, SIGTSTP, SIGCHLD), and a full set of built-ins including job control (fg/bg), history, and environment variable management.
Operating System Simulation
Engineered a UNIX-like OS kernel in C from scratch — implementing 4 scheduling algorithms (FCFS, SJF, Round Robin, Priority), IPC via semaphores and shared memory, and hardware interrupt simulation managing 50+ concurrent process contexts.
JIRA-Inspired Project Management Tool
Shipped a collaborative project management platform supporting real-time sprint tracking and task workflows across multi-user teams — powered by Django and Socket.io, deployed on AWS with sub-second update propagation.
OneLiner — Reddit Hackathon
Built a full-stack Reddit-integrated app with sub-100ms backend APIs using Redis caching. Served 1,000+ potential users and reduced runtime errors 40% via TypeScript strict mode.
- AI system evaluation, reliability, and reducing hallucination in production RAG pipelines
- Automation in risk, compliance, and enterprise workflow systems
- Scalable backend architecture and cloud infrastructure design
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.