About Hunter

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Remote Work, USA

Professional Summary

I am a software engineer with over 5 years of experience.
I specialize in developing large-scale, efficient software solutions across multiple platforms.
Over my career, I have worked in a wide array of programming languages, particularly TypeScript, C#, Java, SQL, and Python.
I have a strong background in data structures, Agile methodologies, and RESTful APIs.
Attention Recruiters: I am very happy in my fully remote position.
- Please do not contact me with in-office work or low-ball offers.
- Please do not contact me about "AI startups" that are just API wrappers over OpenAI, Anthropic, or similar services.

Lease Decisioning Service: Architected a production async REST API (FastAPI/Python) orchestrating real-time lease application credit decisions; managing a stateful task collection engine, task autofill integration, and an external decision engine across a PostgreSQL-backed async ORM with idempotent request handling and PII masking.
- Reduced customer sign-up friction across all lease application decisions by progressively taking ownership of the full application flow, now handling significant production traffic.
Plaid Financial Integration Microservice: Drove measurable GMV growth by building a full-lifecycle bank verification microservice (FastAPI/Python) managing Plaid Link sessions, webhook processing, CRA report generation, and downstream workflow orchestration.

Lead AI Initiatives: Designed and built Range's LLM-powered chat service, enhancing financial planners' efficiency by streamlining member context gathering and decision support.
AI Strategy & Infrastructure: Spearheaded the development of Range's AI strategy, establishing automation pipelines and AI-driven workflows that serve as the foundation for scalable intelligence across the company.
LLM Performance & Evaluation: Developed in-house AI evaluation frameworks using PromptFoo, LangSmith, and custom methodologies, ensuring data-driven improvements in RAG, MCP (Model Context Protocol), and Tool Use.
Full AI Stack Development: Engineered end-to-end automation pipelines for AI-driven financial insights, integrating OpenAI, Anthropic, and Gemini models, alongside a GraphQL-based Pub/Sub architecture for real-time chat.
Subject Matter Expert in Applied AI: Owned the integration of RAG, Tool Use, and custom API connectivity, ensuring LLM deployments go beyond simple wrappers to deliver high-impact, production-ready AI solutions.

Project - Cross-Dealer Groups: Engineered and deployed a system for enterprise business groups that contain multiple security dealers.
Project - Single System Logins: Led the development of an enterprise-scale, highly performant logins management system project.

Improved performance tenfold: Reduced load time from 32 seconds down to 0.2 seconds for over 1800 logins.
Modernized legacy code: Built a fast, modern customer interface in Ember.js using Typescript and Handlebars.
Mobile-first development: Developed mobile webviews in native mobile application, synchronizing with web application.

Cross-Team Collaboration: Coordinated with mobile developers to build synchronized web and mobile application pages, achieving a consistent user experience across all devices.
Feature Engineering: Developed advanced product features focusing on user management, specifically tailored for enterprise clients.
Performance Tracking: Monitored ticket metrics for performance and increase customer usage, leading to a 20% increase in user satisfaction as reported by security dealer feedback.
Beta Development: Partnered with quality engineers and product managers to develop beta features, maintaining a patch rate of under 10%.

Project - Monitoring Systems: Designed and implemented confidential C and C++ systems monitoring and data management tools for submarines with an expected service life of 42 years.
Project - Automated Testing Software: Developed Java-based virtual testing platforms and an automation tool, adopted by five additional developers, enhancing productivity by 20-25%.
Hardware Systems: Built systems for long-term hardware deployment and monitoring, following government procedures and testing documentation.

Project - PDMP Retrieval Automation: Created an automated workflow using Python scripts to securely retrieve confidential patient data, achieving 100% automation of the task while maintaining all HIPAA procedures.
Feature Engineering: Communicated directly with CTO and fellow team members to implement novel HIPAA-compliant features.