Jerome Hardaway
Software Engineer & Veteran Advocate
Based in Atlanta, transforming the tech industry through code and community.
About Me
I'm a builder who doesn't just create things; I connect them.
With a deep command of UI, Data Engineering, and AI Engineering, I specialize in crafting systems where each layer supports the next, and all of it serves the user. My background allows me to bridge the gap between intuitive design, reliable infrastructure, and intelligent automation. That connection is where the real magic happens.
I design interfaces with tools like React, Next.js, and Tailwind CSS that feel invisible because the best UI doesn't call attention to itself; it delivers value. I build data pipelines that quietly power those experiences, taking in real-time signals, structuring them, and ensuring they land where they matter. I integrate AI through platforms like Google Gemini and Azure OpenAI to surface intelligence at just the right moment, whether that's through language models, recommendation systems, or automation agents.
For the past three years, I've worked at scale in both Data and AI Engineering, building solutions that work across contexts—internal tools, external platforms, and direct-to-human products. I'm just as comfortable designing workflows for a company dashboard as I am creating AI-powered translators or misinformation detectors.
But the heart of it is this: I make complex systems feel simple. I believe in building technology that gets out of the way so the user, whether it's a company, a team, or a single person, gets what they need with clarity and speed.
I build at scale. I connect with intention. I deliver with impact.
My Skills & Tools
I’ve spent the last decade evolving into what I call a Triple T-shaped engineer, someone with deep, battle-tested expertise in UI, Data, and AI. My journey started in government, working as a data analyst at the Department of Homeland Security, where I learned how to turn raw information into decision-making tools. That experience taught me the importance of structure, security, and clarity in everything I build.
But I wanted to create things people could see and touch, so I leaned into front-end development, teaching myself jQuery and Bootstrap and building interfaces that made complex tasks feel simple. I followed that passion to a dev shop where I picked up WordPress and Rails, and sharpened my product sense through client work. A pivotal moment came when I earned a LinkedIn engineering award that sent me to New York for a year of intense growth, focused on transitioning from a coder to a systems-thinking engineer. During that period, Node.js was gaining traction, and the front-end landscape was exploding. I mastered Angular, Ember, and Backbone, learning how to stitch them into backend services and bring full-stack apps to life.
Discovering React changed everything. Its component model aligned with how I naturally solve problems, and it fueled my love for building clean, elegant UIs that scale. But even as I deepened my UI skills, I stayed close to the data. When Microsoft reached out, it opened the door to work at enterprise scale. My first project was in retail, using Scala to build reliable data flows in a high-throughput environment. Next, I led efforts on a global cloud modernization initiative for the automotive space.
Then I took on a project that let me go end to end on data engineering. I built pipelines that connected data lakes to data warehouses, designed and automated ETL flows, implemented DevOps processes, and wrote tests to ensure data quality and resilience at every layer. That was the project that made me fall in love with data engineering and pushed me deep into Python, distributed systems, and ML tooling.
From there, I worked on two high-impact projects with a major international retail brand. One focused on machine learning and product intelligence in the U.S. market. The other, built for the China market, introduced me to real-time computer vision systems and required optimizing performance across interfaces used by hundreds of people simultaneously. I followed that with an internal tool that evaluated the quality of code generated by AI, helping teams assess reliability and correctness.
My final project at Microsoft combined everything. I used Python, React, Node, and Azure AI to create an enterprise-grade AI system that enabled large organizations to place complex event-based orders through a natural language interface.
Today, I see my strength not in one discipline, but in how I bring them together. UI makes my work intuitive, data makes it reliable, and AI makes it adaptive. Being a Triple T-shaped engineer means I can speak all three languages fluently and use them to build technology that feels human, moves fast, and scales with purpose.