erin.dev
AI Product Engineer

Erin Burke

I build AI systems that fail gracefully and improve continuously.

Guardrails catch the bad outputs. Feedback loops fix the root cause. I engineer both - the safety layers that protect users today and the human-in-the-loop systems that make the model better tomorrow.

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Illustration of a developer coding with coffee
Illustration of a developer coding with coffee

About Me

The abridged version

Headshot of Erin Burke

I build AI-powered tools that people actually want to use. That means I care as much about API design and interaction patterns as I do about model orchestration — because the hardest part of shipping LLM features isn't the AI, it's everything around it.

My background is full-stack (React, TypeScript, Python, FastAPI), and I've spent the last year focused on LLM application architecture: multi-model pipelines, evaluation infrastructure, streaming interfaces, and the unglamorous plumbing that turns a promising demo into a reliable product.

I'm drawn to problems where product thinking and engineering depth have to coexist — where you can't just throw a model at it and call it done.

Projects

Selected work — things I've built and learned from.

🪾 Weirwood.net

Repo Live

AI-powered literary analysis engine for A Song of Ice and Fire prophecies

React 18TypeScriptFastAPIPython 3.12+10

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A personalized book ranking engine that surfaces the right book at the right time

PythonFastAPIReactTypeScript+8

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Test your LLM defenses against real-world prompt injection attacks

Python 3.12FastAPIPydantic v2SQLite / aiosqlite+10

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Multi-criteria argument ranking with LLM-as-judge evaluation

React 19TypeScriptChakra UI v3Recharts+9

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An interactive exploration of the cold-start problem in recommendation systems

Python 3.12FastAPIscikit-surprise (SVD)scikit-learn+11

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Data-driven health scores for open-source projects — because star count is a terrible signal

Python 3.12FastAPISQLAlchemy (async)PostgreSQL+11

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Interactive token budget visualizer with AI-powered context window optimization

React 19TypeScript 5.9D3.jsZustand+6

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What would a medieval monk think of TikTok? Ask him yourself.

React 19TypeScriptFastAPIPython+7

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Red-teaming framework that stress-tests LLM guardrails against the OWASP Top 10

Python 3.12+Pydantic v2asyncio / httpxTyper + Rich+9

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Paste any recipe. Plan a week. Get one grocery list. Powered by chained GPT-4 tool calls.

Python 3.11FastAPISQLAlchemy 2.0 (async)PostgreSQL 16+12

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A terminal-based philosophical sparring partner that questions your reasoning instead of answering your questions

Python 3.11GPT-4 (OpenAI API)tiktokenPrompt Engineering+1

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AI-powered job posting analyzer that extracts structured data and scores your fit

React 19TypeScriptTailwind CSS v4Vite+11

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Turn Wikipedia rabbit holes into interactive knowledge graphs

**FastAPI****SQLite****NetworkX****OpenAI GPT-3.5 Turbo**+4

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Search your local docs with natural language — not keywords

Python 3.11ClickOpenAI API (ada-002 + GPT-4)ChromaDB+4

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A two-stage LLM pipeline that transforms raw morning dream notes into illustrated journal entries using GPT-4 and DALL-E 3

Python 3.11OpenAI SDK v1.x (GPT-4 + DALL-E 3)Pydantic v2Click+4

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Turns bank CSV exports into AI-generated spending narratives — because pie charts don't tell you that you ordered DoorDash three nights in a row

Python 3.11GPT-4 Turbo (128K context)OpenAI SDK v1.0+pandas+3

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Bidirectional emoji-text translator powered by embedding-based semantic search

Python 3.11NumPyOpenAI ada-002 EmbeddingsGPT-3.5 Turbo+4

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Skills & Tools

Technologies I work with regularly. Strongest in TypeScript and React on the frontend, Python and FastAPI on the backend, with growing depth in LLM application development.

Languages

TypeScript

JavaScript

Python

Frontend

React

Next.js

Chakra UI

Tailwind CSS

Framer Motion

D3.js

Vite

Backend

Node.js

FastAPI

PostgreSQL

SQLite

SQLAlchemy

Pydantic

Redis

AI & ML

Claude API

OpenAI API

LLM Engineering

Infrastructure

Docker

GitHub Actions

Vercel

Linux

Tools

Git

GitHub

pytest

Vitest

Experience

Where I've been and what I've built along the way.

Professional

Member of the Technical Staff

Latest

Norm AI - LEAP (Legal Engineering Automation Platform) Team

Sept 2024 – Dec 2025

Early engineer on the LEAP team building human-in-the-loop feedback systems for optimizing performance in our AI compliance agent, transforming complex regulations into structured LLM feedback loops that continuously improve model outputs and reduce compliance risk for our enterprise customers.

  • Designed, shipped, + iterated on AI-automated workflows for legal agent deployment teams, reducing client onboarding time by 70%
  • Built custom evaluation benchmarks and validation datasets with regulatory domain experts, improving agent accuracy on document processing + compliance analysis.
  • Led development of microservices in Python and FastAPI, scaling to thousands of concurrent tasks under p99 latency SLAs.
  • Designed PostgreSQL schemas, indexes, query patterns for document metadata + compliance audit logs, maintaining performance at scale

Full-Stack Engineer

Rapid7 - Insight Cloud Security

May 2022 - Aug 2023

Developed customer-facing security tooling on Rapid7's Insight Cloud platform — visualizing high-volume threat data and shipping features safely to enterprise accounts through progressive rollouts.

  • Processed + visualized high-volume security event data (100K+ events/day) in customer-facing dashboards, designing efficient query patterns + data aggregation strategies
  • Implemented client-side state management for complex security dashboard views using Redux, handling real-time data updates across 10K+ concurrent user sessions
  • Drove adoption of feature flagging for progressive rollouts in a security-critical environment, enabling safe deployment of new detection rules to enterprise accounts

Associate Product Manager Intern

Atlassian - Trello-Slack Integrations

May 2021 - Aug 2021

Started career building internal tools and automating workflows. First exposure to full-stack development, API design, and production deployment.

  • Analyzed Trello Power-Up usage data to prioritize which board actions to surface in Slack, focusing on the top 5 actions that covered ~80% of daily user workflows
  • Owned the product spec for Trello's Slack integration, defining notification logic, card creation flows, and board action commands that shipped to 10M+ Trello users
  • Built functional prototypes of Slack bot interactions (slash commands, interactive buttons, card previews) using Node.js and Slack's Block Kit API to validate UX flows before engineering handoff
  • Mapped the end-to-end user journey across Trello and Slack, identifying 3 critical drop-off points in the notification-to-action flow and proposing solutions that improved estimated engagement by ~20%
  • Coordinated cross-team alignment between the Trello product team and Slack partnerships team, running weekly syncs and maintaining a shared decision log to resolve 10+ integration scoping conflicts

Associate Product Manager Intern

Atlassian - Confluence-Jira Integration

May 2020 - Aug 2020

Started career building internal tools and automating workflows. First exposure to full-stack development, API design, and production deployment.

  • Instrumented product metric pipelines using Amplitude, writing custom SQL queries to track feature adoption across 15K+ users
  • Built internal analytics dashboards to surface real-time KPIs, reducing stakeholder reporting overhead by 60%
  • Designed A/B testing framework with engineering, specifying event schemas and statistical significance thresholds for feature rollouts
  • Conducted competitive analysis of 5+ collaboration tools and synthesized findings into a product brief that informed the integration roadmap, presented to senior product leadership
  • Led user research with 15+ enterprise customers to identify pain points in the documentation-to-issue-tracking workflow, surfacing insights that shaped the embed experience and inline editing capabilities

Research

Memorial Sloan Kettering Cancer Center - Clinic Team

Harvey Mudd College

Aug 2021 - May 2022

Collaborated with researchers + clinicians at Memorial Sloan Kettering to build 15+ data analysis and visualization tools for single-cell RNA sequencing workflows

  • Collaborated with researchers + clinicians at Memorial Sloan Kettering to build 15+ data analysis and visualization tools for single-cell RNA sequencing workflows
  • Built reproducible analysis pipelines processing high-dimensional data (20K+ genes × thousands of cells) using Pandas, NumPy, scikit-learn, and custom dimensionality reduction methods
  • Designed eval frameworks validating cluster quality against known markers, establishing statistical baselines for anomaly detection

Combinatorics Research Assistant

Claremont McKenna College Mathematics Department

Jan 2022 - May 2022

Researched novel applications of Markov Chain Monte Carlo methods to graph partitioning problems in the context of political redistricting, resulting in a co-authored publication in a peer-reviewed mathematics journal.

  • Modeled redistricting as a graph partitioning problem, implementing Markov Chain Monte Carlo sampling algorithms to explore exponential combinatorial state spaces
  • Built full analysis pipeline in Python (NetworkX, NumPy, Matplotlib) computing transition probabilities via spanning tree theory and analyzing stationary distributions

Academic

Managing Director

Claremont Consulting Group

Jan 2019- May 2022

Student-run, revenue-generating consulting organization serving clients across industries. Worked as Associate Sales Director, Project Lead and Managing Director.

  • Managed a team of student consultants across multiple concurrent client engagements, owning project scoping, delivery timelines, and stakeholder communication.
  • 2x'd annual revenue by building a targeted outbound sales pipeline, closing 10 new client engagements in one year.

Teaching Mentor

Murty Sunak Quantitative and Computing Lab

Sept 2019 - May 2022

Offer both group and individual tutoring and mentoring in computer science, data science, and quantitative subjects to students across the 5C's.

  • Mentored 20+ students one-on-one in Python, data analysis, and introductory ML — translating abstract concepts into concrete, working code.
  • Designed and ran weekly workshops on foundational CS topics, emphasizing hands-on problem-solving over lecture-style instruction.

Education

Academic background.

B.A. Computer Science

Claremont McKenna College - major coursework completed at Harvey Mudd College

May 2022

Focused on systems programming and software engineering. Coursework included distributed systems, compilers, and human-computer interaction.

Contact

Have a question or want to work together? Drop me a message.