Contracted as an AI Solutions Architect to build from scratch an AI system that provides product recommendations backed by specific data, branding, and data that is not present in the current AI models training data.This work was contract work through multiple clients for a large chip maker and a big-box retailers website as an end-user soltuion.

• 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐨𝐟 '𝐌𝐢𝐥𝐭𝐨𝐧': Built and deployed a diabetic AI chatbot using SMS.• 𝐑𝐀𝐆 𝐒𝐲𝐬𝐭𝐞𝐦 𝐈𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: Established a Retrieval-Augmented Generation (RAG) system using Zep Memory for AI development.• 𝐀𝐫𝐜𝐡𝐢𝐭𝐞𝐜𝐭𝐮𝐫𝐞 𝐃𝐞𝐬𝐢𝐠𝐧: Engineered the infrastructure for the SMS-based chatbot using AWS lambdas, Twilio and Serverless Framework.• 𝐀𝐏𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Crafted APIs for a customer dashboard to display user metrics, message exchanges, and user invitations.• 𝐏𝐫𝐨𝐭𝐨𝐭𝐲𝐩𝐞 𝐄𝐧𝐡𝐚𝐧𝐜𝐞𝐦𝐞𝐧𝐭: Advanced an initial prototype, improving conversation flows and system functionalities in 'Milton'.• 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐯𝐞 𝐂𝐡𝐚𝐢𝐧 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧: Developed 7 diverse chains in 'Milton', employing precise prompts and structured data techniques.• 𝐒𝐲𝐬𝐭𝐞𝐦 𝐃𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧: Created architectural diagrams to showcase 'Milton's ecosystem and operational processes.• 𝐂𝐡𝐚𝐭𝐛𝐨𝐭 𝐂𝐚𝐩𝐚𝐛𝐢𝐥𝐢𝐭𝐢𝐞𝐬: • 𝐂𝐨𝐧𝐯𝐞𝐫𝐬𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐈𝐧𝐭𝐞𝐫𝐟𝐚𝐜𝐞: Enabled interactive, user-friendly dialogues. • 𝐃𝐢𝐚𝐛𝐞𝐭𝐢𝐜 𝐌𝐞𝐭𝐫𝐢𝐜𝐬 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: Logged key diabetic metrics like glucose levels, meals, and exercise routines. • 𝐅𝐨𝐨𝐝 𝐈𝐦𝐚𝐠𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠: Transformed food images into detailed meal logs. • 𝐔𝐬𝐞𝐫 𝐈𝐧𝐭𝐞𝐧𝐭 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Determined user message intentions and categorized messages effectively. • 𝐒𝐦𝐚𝐫𝐭 𝐑𝐞𝐦𝐢𝐧𝐝𝐞𝐫 𝐒𝐲𝐬𝐭𝐞𝐦: Implemented intelligent reminders based on user data. • 𝐇𝐢𝐬𝐭𝐨𝐫𝐢𝐜𝐚𝐥 𝐌𝐞𝐚𝐥 𝐋𝐨𝐠𝐠𝐢𝐧𝐠: Enabled logging of meals for past dates. • 𝐃𝐲𝐧𝐚𝐦𝐢𝐜 𝐄𝐦𝐨𝐣𝐢 𝐑𝐞𝐜𝐨𝐠𝐧𝐢𝐭𝐢𝐨𝐧: Interpreted and responded to user emojis or reactions in context. • 𝐒𝐦𝐚𝐫𝐭 𝐑𝐞𝐬𝐩𝐨𝐧𝐬𝐞 𝐌𝐞𝐜𝐡𝐚𝐧𝐢𝐬𝐦: Designed a response system to handle multiple chain outputs intelligently.

Built a video captioning and searching web app with 1 other engineer. I architected and built the brunt of this project and brought on this other engineer months later to help refine the front end. This app is built using AWS services with a Python framework called Masonite Framework. It is fully scalable and capable of handling large file uploads as well as operating on those files in parallel. The architecture was reviewed by the AWS WAR team and they gave it the 2nd best architecture they have reviewed since doing reviews for AWS. This company (Quicc) was recently accepted into the Comcast SportTech Accelerator. Only 10 companies are chosen out of 1000+. Comcast was highly impressed with the product only coming from a team of 4 (CEO, CTO, Founding Engineer, Full Stack Engineer). The platform is capable of 6GB of videos (artificial limit, which could be higher) and 4 hours in duration (hard limit at the moment). Once ingested, the video(s) transcript is searchable and clipable. I cannot give technical details of how but rest assured this is fully scalable and HA.

I worked on multiple projects at Zant. The first project was Preact and Golang stack. I had no experience in Golang which is where I worked primarily on. The dev shop did not either and could not find anyone with experience. I learned Golang and optimized the existing codebase which ended up helping the company earn an extension to their contract with the client. I helped set up a readme (which it lacked) for future engineers and helped onboard the other engineers. I was the team lead for this project for the Front and Back ends. We hit several deliverables and handled large scope creep from the client when it came to payment processors. After this project, I was moved onto a brand new client project to help scope, architect, and build the MVP. This project wraps up on the 31st where I am currently migrating things over to the client for hand-off. This was a Python and Django backend and React Native Mobile App front. I architected the AWS infrastructure and built the backends. This was a video streaming app with HIPAA compliance. I have many years of HIPAA compliance apps I have written/worked on. I am not officially certified though. This app has a real-time direct messaging feature using Websockets. It also has the ability to upload recorded videos as well as stream through the app. App is built for Android and iOS.

Client for my LLC - Press Start. I helped build a platform for a social media growth company. I reversed engineered some applications written by a previous engineer and integrated the API. I also built an SMS integration that helped streamline some customer experiences. (Vague description due to client privacy)

Client for my LLC - Press Start. I managed and modified their current invoicing platform that used QuickBooks API.

Client under my LLC - Press Start. I helped with old SNT Media tech. I built a machine learning model that is able to consume a web page, scrape it, and digest the text. Then it spits out a category it thinks the article is in. IE, sports, politics, weather, etc. Worked on other various tasks.

Client under my LLC - Press Start. Building Video Processing software in conjunction with machine learning models.

I was a contractor for TopDevz and work on their clients projects. Current project worked to integrate QBO REST API with the clients custom WebApp. Uses Oauth 2.0 for authorization. Clients project was on a laptop, moved to AWS EC2 instance.

My roles are to develop usable content to drive our widget based ad stack. This includes writing PHP APIs to managing data in MYSQL or MongoDB.

I joined the R&D group of 4 to steer SNT Media into better more advanced directions. My role is to provide strong research of a given task and provide a working proof of concept.

Design, Develop, Debug existing and new projects/code base in PHP or Python. Setup LAMP and WAMP stacks for testing, live or dev environments. Familiar with Cpanels, CMS, and CLI in Debian or CentOS.

Test bugs from a bug tracker, build test cases for new features, report major bugs to senior testers