Software Engineer
Hi, I'm Michael Jamieson.
5+ years building data pipelines, developer tools, and cross-platform apps with TypeScript, React, Node.js, Python, and PostgreSQL.
Data integration
Turning messy external data into clean, validated internal records.
Developer tools
Internal tooling adopted by engineering teams across domains.
Cross-platform
Web, mobile, and desktop apps that ship together.
Featured Work
Selected projects
Recent builds across data-pipeline tooling, Electron desktop apps, and React Native mobile work shipped to the App Store and Google Play.
Solving integration problems end to end.
I specialise in solving complex integration problems - taking messy, inconsistent external data and transforming it into clean internal records. I've built data transformation pipelines, validation platforms, and developer tools across public safety, healthcare, and supply chain domains.
I've built internal tools adopted by engineering teams, co-founded a startup, and shipped consumer products used in NYC public schools. I'm comfortable owning the full lifecycle - architecture, implementation, and release management - and happiest when I can learn quickly and ship software that makes a real difference.
What I bring to a team
A mix of languages, frameworks, and platforms I reach for most often.
Languages
- TypeScript
- JavaScript
- Python
- Java
Frontend & Mobile
- React
- React Native (Expo)
- Next.js
Backend & Data
- Node.js
- Flask
- Spring Boot
- PostgreSQL
- MySQL
- Liquid Templates
Platforms & Tooling
- Electron
- Docker
- Git
- Vitest / Testing Library
Latest posts
Notes from recent work - debugging, tooling, and the occasional deep dive.
pgvector: Vector Search Inside Postgres (No Extra DB)
Why pgvector lets Postgres do vector search itself - a vector column type, distance operators, and IVFFlat vs HNSW indexes - so most projects never need a separate vector database.
LangSmith: Close the Loop Between Shipped and Working
LangSmith's agent engine closes the gap between shipped and working: it clusters production failures into named issues, traces each back to the commit that introduced it, and drafts a fix that waits for your approval.
Tavily For Beginners: Give Your AI Real-Time Web Search
Tavily gives a language model real-time web search in four lines - structured results with a synthesized answer field, search-depth and time-range knobs, and a first-party LangChain tool.
Running A RAG Pipeline On The Pentagon UFO Files — Real Cypher, Real Citations
Episode 2: open the actual repo and run all six stages on 115 declassified PDFs — Chroma retriever returns cited answers and a FalkorDB graph agent writes Cypher from plain English.
Teach AI To Read UFO Files (LangGraph + RAG)
Episode 1: the architecture of a six-stage RAG pipeline plus a GraphRAG layer in LangChain + LangGraph, built to read 4 GB of declassified UFO files on a single workstation.
Open to opportunities.
Interested in software engineering roles focused on data integration, developer tooling, or cross-platform product work. I thrive in environments where data accuracy and reliability are non-negotiable.