Frontend
- React.js
- TypeScript
- JavaScript
- HTML
- CSS
- Responsive UI
- Component architecture
Brian E. Kane
11+ years building software with React, Java, backend services, and modern AI systems including RAG, embeddings, machine learning, and agentic workflows.
AI Digital Twin is live. Ask it about my background, projects, and engineering experience.

Serious about engineering.
Not overly serious about myself.
I am a software engineer with over 11 years of experience building reliable applications, APIs, and front-end systems. My core background is React.js for the front-end and Java for the backend/service layer. I have been expanding deeply into AI engineering for the last 2+ years, including machine learning, RAG, embeddings, LLM applications, agentic AI systems, MCP primarily as tools for AI agents.
I take my work seriously: clean architecture, maintainable code, thoughtful UX, and systems that actually solve business problems.
I do not take myself too seriously, which means I enjoy collaboration, humor, and working with people who like building things the right way without turning every meeting into a ceremony.
Grouped by practice area — no vanity percentages, just what ships.
Some of the personal projects I've been working on recently.
Full-stack portfolio assistant
Portfolio-grade conversational AI that answers as Brian's professional digital twin. Next.js frontend, typed FastAPI backend, AWS Bedrock (Amazon Nova), session memory (local JSON or S3), Terraform-managed AWS infrastructure, and GitHub Actions deployment with OIDC from a public repo. Demonstrates applied AI orchestration, cloud engineering, and controlled deployment—not a generic chatbot wrapper.
AI-Assisted Paper Trading Platform
Full-stack paper-trading platform with a React SPA, FastAPI backend, and OpenAI Agents SDK orchestration. Morning briefings flow through a deterministic pipeline: candidate scoring, market data, portfolio state, risk rules, then structured AI recommendations with a full decision ledger. Demonstrates responsible AI (manual/assisted/autonomous modes), cost-aware LLM usage, InstantDB persistence, WCAG-tested UI, and Vercel + Render deployment.
RAG Document Assistant
Portfolio RAG app that answers questions from a controlled document corpus and subjects each answer to adversarial review: Witness generates grounded responses, Prosecutor challenges claims, and Judge delivers transparent verdicts with citations. Demonstrates hybrid retrieval, multi-agent orchestration, claim-level verification, document ingestion, and an evaluation dashboard.
Interactive insurance knowledge base demo
Explore a fictional insurance company's document corpus (contracts, products, employees). Switch between embedding models to compare retrieval behavior, visualize the vector store in 2D and 3D t-SNE plots, and ask grounded questions with cited sources.
Plan visits to U.S. national parks with an interactive assistant powered by structured park data and LLM-driven suggestions.
Healthcare-focused AI assistant that turns clinician consultation notes into structured visit summaries, doctor next steps, and patient-friendly email drafts. Inference uses Ollama in a private Docker container on the backend so notes are not sent to third-party LLM APIs, supporting a PHI/PII-conscious demo path (synthetic data only).
My AI work focuses on practical applications of modern AI systems: RAG, embeddings, LLM-powered applications, agentic workflows, and AI-assisted development. I am especially interested in turning AI demos into reliable systems with clear architecture, useful UX, and maintainable code.
Intern → Software Analyst → Senior Software Analyst → Software Advisor
PDF is the primary format for recruiters and ATS.
Readable in the browser, good for quick scanning.
Ask about my background, projects, tech stack, and engineering decisions — backed by a deployed full-stack AWS Bedrock application.
Live text chat on AWS — ask about my resume, projects, and AI engineering work.
Serious about engineering. Less serious about hats.
I build production software, AI systems, and occasionally questionable fashion decisions.

Open to senior software engineering, full-stack engineering, AI engineering, and agentic AI application roles.