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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8" />
<title>Jeffrey Flynt | Create then Iterate</title>
<meta name="description" content="Full-Stack JavaScript Developer based in Austin, TX." />
<meta name="viewport" content="width=device-width, initial-scale=1, maximum-scale=1, minimal-ui" />
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="apple-mobile-web-app-capable" content="yes" />
<meta name="apple-mobile-web-app-status-barstyle" content="black-translucent" />
<meta name="apple-mobile-web-app-title" content="Jeffrey Flynt" />
<meta name="mobile-web-app-capable" content="yes" />
<link rel="stylesheet" href="libs/font-awesome/css/fontawesome.css" type="text/css" />
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<link rel="stylesheet" href="assets/css/app.min.css" type="text/css" />
</head>
<body>
<header>
<nav class="navbar fixed-top justify-content-start m-lg-4">
<a href="#home" data-scroll-to="home" class="navbar-brand navlogo dark-white m-0 r-l">
<span class="hidden-folded text-red d-inline">Jeffrey Flynt</span>
</a>
<ul class="nav white px-3">
<li class="nav-item">
<a class="nav-link px-2" href="#mywork" data-scroll-to="mywork">
<span class="navfont">My Work</span>
</a>
</li>
<li class="nav-item">
<a class="nav-link px-2" href="#education" data-scroll-to="education">
<span class="navfont">Education</span>
</a>
</li>
<li class="nav-item">
<a class="nav-link px-2" href="#articles" data-scroll-to="articles">
<span class="navfont">Articles</span>
</a>
</li>
<li class="nav-item">
<a class="nav-link px-2" href="#challenges" data-scroll-to="challenges">
<span class="navfont text-red">Competitions</span>
</a>
</li>
</ul>
</nav>
</header>
<div class="padding">
<div class="row" id="home">
<div class="col-md-6 white h-v-50 d-flex">
<div class="p-5 flex align-self-center">
<h1 class="display-4 _700 l-s-n-1x my-5">Senior <span class="text-red">Full-Stack</span> Software Engineer
</h1>
<h5 class="mb-5"><span class="home-text">Accomplished Senior Full-Stack Engineer and Founder with a proven history of developing innovative platforms, leading significant technical migrations, and achieving substantial cost reductions. As Founder of RapidVerify, I built a real-time identity and income verification platform, integrating it with major business systems. At LitX, I spearheaded MVP development for the legal sector, demonstrating high productivity and ensuring HIPAA/SOC II compliance. My work at CapX included a <b>60% reduction</b> in MongoDB query times and CI/CD migration. While at Under Armour, I led a critical transition to a microservices architecture, resulting in an <b>$80k monthly</b> AWS cost saving and a successful database migration.</h5>
<ul class="nav bg">
<a href="https://www.github.com/jeffreyflynt">
<li class=""><i class="fa-brands fa-github fa-3x mr-5"></i></li>
</a>
<a href="https://www.linkedin.com/jeffrey-flynt02">
<li class=""><i class="fa-brands fa-linkedin fa-3x mr-5"></i></li>
</a>
<a href="https://medium.com/@jeffreyflynt02">
<li class=""><i class="fa-brands fa-medium fa-3x mr-5"></i></li>
</a>
<li class=""><i class="fa-solid fa-envelope fa-3x"></i></li>
</ul>
</div>
</div>
<div class="col-md-6 px-lg-5 px-sm-0 align-self-center justify-content">
<img class="img-fluid mx-auto d-block avatar w-lg" src="jeff-flynt.png">
</div>
</div>
</div>
<div class="px-5 dark" id="education">
<div class="box-radius-2 box-shadow-4 no-shadow py-5">
<div class="row p-lg-5 py-5">
<div class="col-12 col-lg-4 col-xl-4">
<h4 class="display-4 _700 l-s-n-1x mb-5">
<span class="text-red">Education</span><br>
<span class="text-muted">and</span><br>
<span class="text-muted">
<span class="text-muted">Training</span>
</span>
</h4>
</div>
<div class="col-12 col-lg-8 col-xl-8">
<div class="row">
<div class="col-6">
<img class="img-fluid w mb-4" src="utaustin.svg">
</div>
<div class="col-6">
<img class="img-fluid w mb-4" src="hilt.png">
</div>
</div>
<div class="row">
<div class="col-6">
<img class="img-fluid w mt-4 mb-4" src="udacity.svg">
</div>
<div class="col-6">
<img class="img-fluid w mt-4 mb-4" src="comptia.svg">
</div>
</div>
<div class="row">
<div class="col-6">
<img class="img-fluid w mt-4" src="udemy.svg">
</div>
<div class="col-6">
<img class="img-fluid w mt-4" src="">
</div>
</div>
</div>
</div>
</div>
</div>
<div class="px-5 light" id="mywork">
<div class="p-lg-5">
<h4 class="display-4 _700 l-s-n-1x my-5">
<span class="text-red">My</span>
<span class="text-muted">
<span class="text-muted">Work</span>
</span>
</h4>
<div class="row">
<div class="col-12">
<h4 class="text-red">Software/Toolkits</h4>
</div>
<div class="col-6">
<h6 class=" my-2">Textalytic</h6>
<p class="text-muted">Browser based text analysis that handles pre-processing, analyzing, and
visualization in an easy to use web interface. (Written in vanilla JavaScript, charts/graphs use
D3.js & Chart.js, table uses Handsontable). Application is broken
out into (5) node.js microservices.
</p>
</div>
<div class="col-6">
<h6 class=" my-2">Stylometry Toolkit</h6>
<p class="text-muted">A browser based toolkit to identify stylistic signatures characteristic of
Latin prose and verse using a combination of quantitative stylometry and supervised machine
learning.
</p>
</div>
<div class="col-6">
<h6 class=" my-2">Anagram Toolkit</h6>
<p class="text-muted">A browser based sequence alignment toolkit for the detection of anagrams in
Latin literature.
</p>
</div>
<div class="col-6">
<h6 class=" my-2">Filum Toolkit</h6>
<p class="text-muted">A tool for identifying verbal resemblances in literature written in JavaScript
that uses FuzzySearch & Levenshtein Distance.</p>
</div>
</div>
<div class="row">
<div class="col-12 mt-4">
<h4 class="text-red">Work Experience</h4>
</div>
<div class="col-6">
<h6 class="my-2">RapidVerify - <span class="text-muted">Founder</span></h6>
<p class="text-muted">- Engineered a user-friendly interface enabling businesses to deploy robust verification processes without requiring extensive technical expertise.
<br> - Employed advanced algorithms and data analytics to ensure accurate, real-time verification, reducing the risk of fraudulent activities.
<br> - Integrated the platform with leading CRM, property management systems, and HR platforms, including Greenhouse, Lever, QuickBooks, DoorLoop, Pipedrive, and HubSpot, facilitating a broader adoption and enhancing user experience.
<br> - Implemented end-to-end data encryption and comprehensive audit trails, successfully meeting compliance standards and ensuring the highest level of data security and privacy for sensitive user information.
<br> - Ensured high availability and platform resilience, achieving 99.99% uptime by architecting and managing the infrastructure on Kubernetes, coupled with robust DevOps automation using Flux for GitOps-driven continuous deployment and automated recovery processes.
</p>
</div>
<div class="col-6">
<h6 class="my-2">LitX - <span class="text-muted">Sr. Full-Stack Engineer</span></h6>
<p class="text-muted">- Led the development of a transformative MVP for legal sector information exchange.
<br> - Spearheaded the architectural design of a robust database schema
<br> - Pioneered the implementation of resumable downloads, enhancing user experience significantly.
<br> - Expertly developed and integrated REST endpoints, coupled with constructing a dynamic front-end using React.
<br> - Instrumented Kubernetes for improved deployment efficiency.
<br> - Documented the entire process meticulously in Confluence, ensuring knowledge transfer and sustainability.
</p>
</div>
<div class="col-6">
<h6 class="my-2">CapX - <span class="text-muted">Sr. Software Engineer</span></h6>
<p class="text-muted">- Build out the internal tool used by employees in React and integrate with the backend.
<br> - Migrate our CI/CD workflow from Jenkins to Github Actions
<br> - Redefined database schema to return smaller responses to the frontend
<br> - Prototype Excel extraction from Financial Statements
<br> - Successfully reduced MongoDB query time by 60% through the strategic use of aggregation pipelines.
<br> - Developed an automated scraper using Puppeteer to source email leads.
</p>
</div>
<div class="col-6">
<h6 class="my-2">Under Armour (projekt202) - <span class="text-muted">Sr. Developer</span></h6>
<p class="text-muted">- Convert Monolithic Python Service to Modern Spring Boot Microservices
architecture.
<br> - Implement CI/CD with Jenkins, Docker, & Kubernetes.<br> - Support React.js UI Framework
for Brand Challenges.
<br> - Utilize tools such as Celery, Rabbitmq, Python, MongoDB, Prometheus, Kubernetes,
Confluence, jira, and bitbucket.
<br> - Meet with product & design teams for Sprint planning & retros.
<br> - Meet with technical leadership for high-level architecture choices.
<br> - Lead team of frontend, backend developers, Android developers, & iOS developers.
<br> - Implement external APIS such as Segment, Snowflake, Amplitude, & Sales Force Marketing
Cloud
</p>
</div>
<div class="col-6">
<h6 class="my-2">UT Austin - QCL Lab - <span class="text-muted">UI/UX & JavaScript Developer</span>
</h6>
<p class="text-muted">- Research literature using machine learning, natural language processing,
bioinformatics, and systems biology.<br> - Implement automated CI/CD with Gitlab & Docker<br> -
Re-write filum tool which uses a technique derived from computational
biology known as sequence alignment, which considers the character-by-character similarity of
phrases in JavaScript.
<br> - Collaborate with the web team on UI/UX.<br> - Automate large literature text file
analysis.</p>
</div>
<div class="col-6">
<h6 class=" my-2">Austin Software Works - <span class="text-muted">Full Stack Developer & ML
Engineer</span></h6>
<p class="text-muted">
- Proficient in PHP/MySQL | JavaScript/MongoDB | Meteor/Nodejs<br> - Develop/Debug/Test custom
applications for business clients<br> - Use R for data analysis and hypothesis testing<br> -
Deploy application code to AWS EC2/RDS
Instances
<br> - Commit code changes to Github via Git<br> - Create visual charts using D3 & tableau<br> -
Create Tensorflow Models in Python<br> - Optimize NVIDIA CUDA Code & OpenMP for GPU computing.
</p>
</div>
<div class="col-6">
<h6 class=" my-2">UT Austin - <span class="text-muted">Project Manager</span></h6>
<p class="text-muted">
- Oversee technicians for VoIP Conversion of 20k phones<br> - Modify/Configure Cisco Switches to
accommodate new VoIP Phones<br> - Converted spreadsheet to efficient PHP/MySQL Data Entry
Workflow<br> - Reduced survey time by 50%
& deployments by 30%<br> - Assist in planning of best practices for site surveys<br> - Ensure
surveys and deployments ran on schedule<br> - Migrate site surveys from Excel to a web based
application
</p>
</div>
<div class="col-6">
<h6 class=" my-2">The I.T. Department - <span class="text-muted">Head Geek</span></h6>
<p class="text-muted">
- Install & Configure CentOS/Ubuntu AWS Instances<br> - Full-Service I.T. Provider to local
Austin small businesses
<br> - Move physical servers to hosted solutions in AWS<br> - Address trouble tickets opened by
customers via email<br> - Utilized tools such as VMWare, Git, HeidiSQL, Putty<br> - Install &
Configure Cisco Routers, Switches & Access
Points
<br> - Implemented VOIP network using Cisco Appliances<br> - Configure and Manage Load Balancers
and SSL Encryption Devices
<br> - Facilitate communication and develop relationships for many cross functional teams
</p>
</div>
<div class="col-6">
<h6 class=" my-2">SolarWinds - <span class="text-muted">Sales Engineer</span></h6>
<p class="text-muted">
- Determine the strategic needs of IT management for enterprises.<br> - Assist customers in
designing network/storage system architecture.<br> - Demonstrate expert knowledge of vendor
specific technologies including VMWare, Citrix,
and Cisco.
</p>
</div>
<div class="col-6">
<h6 class=" my-2">G.S.A. - <span class="text-muted">Computer Technician</span></h6>
<p class="text-muted">
- Deploy new Dell laptops to all of members of the GSA<br> - Backup all user data to fiber
networked NAS drives
<br> - Ensure encryption was set on all user machines<br> - Ensure computers could log onto
encrypted network
<br> - Ensure all user data was restored
</p>
</div>
</div>
<div class="row">
<div class="col-6 col-lg-6 col-xl-6">
<h4 class="text-red">Research</h4>
<h6 class="my-2">OrgForge: A Multi-Agent Simulation Framework for Verifiable Synthetic Corporate Corpora
</h6>
<p class="text-muted">
Evaluating retrieval-augmented generation (RAG) pipelines requires corpora where ground truth is knowable, temporally structured, and cross-artifact properties that real-world datasets rarely provide cleanly. Existing resources such as the Enron corpus carry legal ambiguity, demographic skew, and no structured ground truth. Purely LLM-generated synthetic data solves the legal problem but introduces a subtler one: the generating model cannot be prevented from hallucinating facts that contradict themselves across documents. We present OrgForge, an open-source multi-agent simulation framework that enforces a strict physics-cognition boundary: a deterministic Python engine maintains a SimEvent ground truth bus; large language models generate only surface prose, constrained by validated proposals. An actor-local clock enforces causal timestamp correctness across all artifact types, eliminating the class of timeline inconsistencies that arise when timestamps are sampled independently per document. We formalize three graph-dynamic subsystems stress propagation via betweenness centrality, temporal edge-weight decay, and Dijkstra escalation routing that govern organizational behavior independently of any LLM. Running a configurable N-day simulation, OrgForge produces interleaved Slack threads, JIRA tickets, Confluence pages, Git pull requests, and emails, all traceable to a shared, immutable event log. We additionally describe a causal chain tracking subsystem that accumulates cross-artifact evidence graphs per incident, a hybrid reciprocal-rank-fusion recurrence detector for identifying repeated failure classes, and an inbound/outbound email engine that routes vendor alerts, customer complaints, and HR correspondence through gated causal chains with probabilistic drop simulation.
</p>
<h6 class="my-2">Estimation of potential United States influenza mortality. An agent based model
simulation
</h6>
<p class="text-muted">
Planning of the next influenza pandemic is of vital concern to many public health officials. The
aim is to use an agent based model of influenza in the United States to estimate mortality
should a pandemic occur present day. Models of infectious disease
epidemics have been proven useful in understanding the dynamics of disease transmission,
vaccination strategies, and are constantly used as an apparatus to support decisions made by
public health officials. Using an agent-based
model of Influenza A virus infection, a simulation is created to simulate the effects of two
strains of influenza A causing a pandemic in the United States.
</p>
<h6 class="my-2">Filum: Large-scale identification of literary intertextuality using sequence
alignment</h6>
<p class="text-muted">
Profiling of intertexutal relationships is foundational for literary study. We demonstrate
Filum, a user-friendly tool that employs character-level sequence alignment to detect verbal
parallels with or without lexical overlap. When applied to a database
of more than 1,000 intertextual parallels of known significance from the Latin poet Valerius
Flaccus, Filum is able to recover more than 80% with reasonable specificity and to identify more
than 250 new intertexts previously unrecorded
in the scholarship.
</p>
<h6 class="my-2">Computational Differentiation of Latin Literary Genre</h6>
<p class="text-muted">
This article describes a new quantitative approach to the study of Latin literary genre. Using
computational text analysis and supervised machine learning we construct a detailed stylistic
profile of the vast majority of extant classical Latin literature
and classify works by traditional genre with high accuracy. By examining the statistical basis
for these automated classification decisions, we identify salient stylistic characteristics of
each genre at the level of syntax and
non-content vocabulary. Through a series of case studies, we illustrate how this approach
enables both confirmation at scale of long-appreciated stylistic tendencies and identification
of unrecognized generic signatures.
</p>
<h6 class="my-2">A Stylometry Toolkit for Latin Literature</h6>
<p class="text-muted">
Computational stylometry has become an increasingly important aspect of literary criticism, but
many humanists lack the technical expertise or language-specific NLP resources required to
exploit computational methods. We demonstrate a stylometry toolkit
for analysis of Latin literary texts, which is freely available at www.qcrit.org/stylometry. Our
toolkit generates data for a diverse range of literary features and has an intuitive
point-and-click interface. The features included
have proven effective for multiple literary studies and are calculated using custom heuristics
without the need for syntactic parsing. As such, the toolkit models one approach to the
user-friendly generation of stylometric data,
which could be extended to other premodern and non-English languages underserved by standard NLP
resources.
</p>
</div>
<div class="col-6 col-lg-6 col-xl-6">
<h4 class="text-red">Presentations</h4>
<h6 class=" my-2">How to Do Philology with Computers - <span class="text-muted">Boston, MA</span>
</h6>
<p class="text-muted">
Computational stylometry has aided the work of philologists for over 50 years. From simple word
counts to the latest use of machine learning for authorship attribution, computation offers the
literary critic a wide array of techniques to better understand
individual texts and large corpora. To date, these methods have largely been accessible to
specialists possessing a background in programming and statistics. The Quantitative Criticism
Lab has now designed a user-friendly toolkit
that will allow humanists with no prior training in the digital humanities to obtain a wide
range of philological data about most classical texts and to perform sophisticated quantitative
analyses—all using a simple point-and-click
interface. This presentation will demonstrate some of the experiments and literary critical
insights enabled by the toolkit, and discuss relevant issues of interpretation and statistical
analysis.
</p>
</div>
</div>
</div>
</div>
<div class="px-5 dark" id="articles">
<div class="box-radius-2 box-shadow-4 no-shadow py-5">
<div class="row p-lg-5 py-5">
<div class="col-12 col-lg-4 col-xl-4">
<h4 class="display-4 _700 l-s-n-1x mb-5">
<span class="text-red">Articles</span><br>
</h4>
</div>
<div class="col-12 col-lg-8 col-xl-8">
<div class="row">
<div class="col-12">
<h3><a
href="https://medium.freecodecamp.org/how-i-built-a-complex-text-analysis-app-in-a-month-61917877cd72">How
I built a complex text analysis app in a month</a></h3>
<p>Published via freeCodeCamp - 05/03/2018</p>
<h3><a
href="https://medium.com/@jeffreyflynt02/natural-language-processing-with-spacy-in-node-js-87214d5547">Natural
Language Processing with Spacy in Node.js</a></h3>
<p>Published via Medium - 03/24/2019</p>
<h3><a
href="https://medium.com/@jeffreyflynt02/load-balance-node-js-with-nginx-without-modifying-your-app-bc3ff09a6e70">Load
balance Node.js with Nginx without modifying your app.</a></h3>
<p>Published via Medium - 03/24/2019</p>
<h3><a
href="https://towardsdatascience.com/how-i-integrated-the-instagram-api-in-react-native-e2bd04dd3119">How
I integrated the Instagram Private API in React Native</a></h3>
<p>Published via Medium - 05/27/2020</p>
<h3><a
href="https://medium.com/@jeffreyflynt02/translating-user-generated-content-in-real-time-c0fe2165be99">Translating
User-Generated Content in Real Time w/ AWS Translate</a></h3>
<p>Published via Medium - 08/11/2021</p>
<h3><a
href="https://medium.com/towards-data-science/using-google-bards-api-w-node-421c100a63d2">Using
Google Bard's API with Node</a></h3>
<p>Published via Medium - 04/22/2023</p>
<h3><a
href="https://medium.com/@jeffreyflynt02/enhancing-file-security-in-amazon-s3-54a467f52efe">Enhancing
File Security in AWS S3</a></h3>
<p>Published via Medium - 04/23/2023</p>
<h3><a href="https://jeffreyflynt02.medium.com/stop-using-the-enron-corpus-how-to-generate-realistic-synthetic-corporate-data-for-rag-16d8ae4f4a63">Stop Using the Enron
Corpus: How to Generate Realistic Synthetic Corporate Data for RAG</a></h3>
<p>Published via Medium - 03/04/2026</p>
<h3><a href="https://jeffreyflynt02.medium.com/i-ran-8-rag-pipelines-against-a-benchmark-where-the-ground-truth-is-guaranteed-1cf883561e63">I Ran 8 RAG Pipelines Against a Benchmark Where
the Ground Truth is Guaranteed. Here’s What I Found.G</a></h3>
<p>Published via Medium - 03/17/2026</p>
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Competitions
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<h4 class="mt-5 mb-0"><span class="text-red">Machine Generation</span> of <span
class="text-muted">Analytic
Products</span></h4>
<h6>Finalist</h6>
<h6 class="mt-5"><span class="home-text">The ODNI and OUSD(I) seek to uncover current
capabilities and examine the feasibility of using natural language processing (NLP) and
related artificial intelligence technologies to craft intelligence products with
national security implications. This Challenge poses a representative question to be
answered by respondents using an automated system of their own design.</h6>
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<h4 class="mt-5 mb-0"><span class="text-red">Identify biothreats</span> in <span
class="text-muted">real
time</span> </h4>
<h6>Pending</h6>
<h6 class="mt-5"><span class="home-text">Successful concepts will explore connections between
multiple readily-accessible data sources to develop real-time insights that can improve
public safety responses to emerging biothreats. Warnings will ideally point to signals
that fall within a zero- to ten-day time horizon of first instances of exposure using
timely data sets that become available less than 36 hours after inputs are received.
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<h4 class="mt-5 mb-0"><span class="text-red">Machine Evaluation</span> of <span
class="text-muted">Analytic
Products</span>
</h4>
<h6>Pending</h6>
<h6 class="mt-5 mb-5"><span class="home-text">The Seekers are asking Solvers to describe a
viable technical approach for enabling the automated evaluation of finished intelligence
products. Solvers must provide a well-supported, technology-based justification for how
the proposed solution could—at a minimum—rapidly evaluate and numerically score brief
(1-2 page) analytic intelligence products against the specified criteria with no human
intervention. </h6>
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