DNS

Upon joining, I came up to speed quickly on the stack of the early version of Pull Workbench, which was very buggy but demonstrated the initial ideas and had a solid set of the latest technologies and patterns established in the codebase, providing for a solid starting point.

I was entrusted to aid our CTO in hiring several additional employees, and so I joined and conducted interviews for the first several months while working with the existing team AI + Full Stack to deliver features and solidify the system, with the aim of keeping it fully working with each merge, after playing a little catch-up to fix the early bugs that worried our business partners, giving them confidence that our team could deliver.

From there, I developed full stack features solo or by pairing with team members, and ultimately led a squad of 5 team members alongside a second squad that together comprised our engineering team.

Much of my time went into authoring complex analytics sql queries using the impressive Kysely library, a fluent, typesafe query builder that we used for our postgres and redshift databases. Given the nature of the product, we needed to make decisions on which queries could be run in real time vs. which queries and subqueries would need to be computed offline as part of a network of airflow dags.

On the ML Ops side I advocated for traceability and reproducibility / determinism of all models and artifacts, and integrated with systems that implemented that, such as Airflow to coordinate DAGs of ML training jobs and Sagemaker's metadata API, which we controlled via model lifecycle automations that produced and stored models, artifacts and metadata that were in turn consumed at runtime or in batch by our analytics stack

On the frontend, I helped us deliver an initial version of the Pattern Editor, a UI and set of APIs that users could use to put together their own patterns of interest, such as looking for certain anomalous ranges of quantities that themselves may be derived from other user-defined patterns. This entailed not only a UI that was DAG-aware but also a layer that converted the json representation of these patterns from the frontend into typesafe kyesely queries to be executed against redshift.

My PM and the business wanted to illustrate to other teams that a fast-paced, fail-fast approach where we released daily (as opposed to 1-3 times per year) would serve us much better in that we could learn quickly, iterate and pivot, without huge costly investments into products that did not meet expectations or deadlines.

Before hiring my team, I set up a CICD pipeline and basic framework of a site that could sustain a heavy and intense crawl from google.

New hires all released to production on their first day of work - a principle I had brought to the table, that it should be so automated and simple that someone could set up and deploy a small feature within their first few hours of working at Sourceability.

Our parts and datasheets website, which also incorporated proprietary availability and quality scores, was used - within 3 months of inception - to successfully sell a 3 year Analytics API contract to an international multibillion dollar company, as well as driving organic traffic and learning how to scale to sustain google crawls of the hundreds of thousands of electronic component parts in our inventory while scaling down outside of the crawl / high-traffic moments.

• Full Stack - React, NodeJS, Typescript, Kubernetes, Gitlab
• Functional Reactive Programming - RxJS, highlandjs
• Daily Production Deploys - Canary Deployment w/ K8s
• Constant Collaboration - No “throwing over the wall”
• CI/CD Automation Pipeline - Every user story gets an instant shareable environment
• Coaching / Mentoring / Leading diverse team

A working prototype and specs for how heartpoints would be rewarded and exchanged and linked to "Proof of Good" that could be validated off-chain (since proof of good in this case may for example, be video evidence or other data that is too large to fit onto the chain), using a strategy of hashing the proof and storing the hash and URL of the proof's off-chain content.

A portal bringing together version control, automated test definitions and statuses, quality metrics, jira tickets, CICD jobs, and supportinginfrastructure definitions and status into a single place to aid in release management and devops practices.

Behind the scenes, pipelines made with K8s (Kubernetes), Mesos, Github and Jenkins automatically provisioned environments, deployed our software and ran extensive tests on it, including complex multi-cloud platform scale tests across Google Cloud and AWS as well as on prem with bare metal and Open Stack

We went through several iterations of the website, but our goals were SEO optimization and systematizing the internal booking process with salesforce while exposing certain information about entertainers, acts and availability through the website, and keeping those in sync with entertainer calendars.

With the help of some interns, I designed and built the website from the ground up, and hosted it at Cleveweb.com, the software solutions company I had formed a few years earlier.

montgranite.com - supplier of natural stone website. After assessing their products, we categorized them according to stone type, colors, texture and brand, then I created a MySQL database and an ORM to read/write PHP objects and their relationships from the database and present it as a front-end, which I designed to resemble a piece of marble.

I then hosted the company's website and email for a number of years afterward and actively updated the site on retainer.

Thetaylorcompanies.com had a searchable cataolgue of many pieces of furniture, each with multiple image angles, specs, descriptions, brands, pricing, and delivery schedules. After understanding their needs, I put together a MySQL database, PHP web server with a custom ORM, and an rich frontend with an animated intro page.

At the time, dialup was still the most prevalent form of connecting to the internet, and our users had 28.8k, 26k and 56k modems, running PPP protocol, and some of them had static IPs whereas others used DHCP to assign connection-session long settings.

Users had Linux home directories, FTP accounts, and the option to host apache based vhosts. My job was to be able to leverage our support base and my growing knowledge of the protocols and technology to do Root Cause Analysis and solve their problems. I always took pride in my job and went above and beyond to provide the best Customer Service