Jonathan Abele — Software Engineer

Hi, I'm Jonathan.

I'm a software engineer at FactSet in Boston. I work on NLP pipelines that process hundreds of thousands of articles daily, building systems for sentiment analysis, entity tagging, and automated content curation.

I studied computer science at the University of Michigan and graduated Summa Cum Laude. I like working on problems where software can replace tedious manual work, especially when it involves AI and large-scale data.

jonathanabele17@gmail.com LinkedIn GitHub

Based in: Boston, MA
Role: Software Engineer II
Education: U of M, BSE CS

Experience

Apr 2026 — Present

Software Engineer II

·FactSetBoston, MA

Promoted to SWE II. Continuing to lead AI-driven pipeline development, expanding automated curation systems, and driving data quality improvements across production NLP infrastructure.

Python
AWS
RabbitMQ
Databricks

Mar 2025 — Mar 2026

Software Engineer I

·FactSetBoston, MA

Optimized a high-throughput NLP pipeline processing hundreds of thousands of articles daily. Led end-to-end development of an LLM-based autocuration system processing ~20k articles/day, significantly reducing manual curation. Built internal dashboards and data visualizations for content curators.

Python
AWS
RabbitMQ
LLMs
Databricks

May — Aug 2024

Data Solutions Intern

·FactSetBoston, MA

Built an AI-powered chatbot using RAG architecture with OpenAI models and a Databricks vector database. Developed the Flask backend API and Vue.js frontend for semantic document retrieval and response generation.

Python
Flask
Vue.js
RAG
OpenAI

Projects

Work

1st Place at FactSet Hackathon 2026

FactSet Sidecar

2026

A Manifest V3 Chrome extension that uses NER to highlight companies, executives, and financial instruments in any web article, then surfaces real-time FactSet data in a side panel, no tab-switching required.

LLM Autocuration

2025

An AI validation system serving as the final stage of a production NLP pipeline. Dynamic prompt-driven classification with a three-state decision framework, processing ~20k articles daily.

RAG Chatbot

2024

An AI-powered chatbot that interprets queries, retrieves information from large document sets via semantic search, and generates accurate responses.

Personal

Sentinel

2026

A personal project for understanding agent orchestration and automated GitHub PR review. A Python pipeline where code, not the model, drives control flow: parallel reviewer agents, an evaluation harness, and full request tracing.

FoodLogAI

2026

An iOS calorie tracker (SwiftUI + FastAPI) where you log meals in plain language and the macros are computed deterministically from a food catalog, not guessed by the model. Includes a barcode and receipt pantry plus cost and nutrition insights.