Jacob
Warthen
Building AI systems that protect people, optimize industries, and create new markets. From distributed trading infrastructure to scam prevention at scale.
Versatile by design.
Technical by nature.
At 24, I have spent the last few years building AI systems across petroleum engineering, financial markets, healthcare, and consumer security, not because it was easy, but because I chose the hardest problems available to me at each stage.
I started at Analog Computation Enterprise as an intern while finishing my CS degree in three years at USF. Within months I was the primary developer on production systems, regularly self-teaching entire domains such as Modelica, Wolfram Language, digital signal processing, and MATLAB to deliver high quality results.
After ACE I went deep on algorithmic trading, building a full live-trading infrastructure in C++ and Python, including co-located servers, custom backtesting, and real-time signal processing, before joining Jump Partners as co-founder and chief engineer to build the first vertical, MyProtection.AI.
I work long hours because the problems are that interesting. The goal is to build something that genuinely changes how people interact with technology, starting with AI that protects them.
Where the work
has taken me.
Building...
Led all software development across multiple AI-driven verticals under the Jump Partners holding company. Primary focus on MyProtection.AI, a scam prevention platform with 200+ users, and XEO Labs, an AI search optimization product. Responsible for full-stack architecture, cloud infrastructure, and technical strategy across both ventures.
Joined as an intern during the final year of my CS degree and grew to lead the most complex client-facing projects. Built production AI systems across petroleum engineering, healthcare, and financial markets using the proprietary Octopus Neural System (ONS), a sensor-based AI grounded in Nash equilibrium theory rather than traditional deep learning.
Founded and fully AI-automated a digital marketing business which funded my CS degree. Developed software to run client campaigns end-to-end with minimal manual work. Profitable, but wound down intentionally to pursue deeper technical work.
Systems built.
Problems solved.
Each project required learning a new domain from scratch and delivering production-grade results.
End-to-end scam prevention platform with real time email, text, and call screening. Email provider agnostic. AWS EKS backend, Kafka event streaming, federated learning loop enabling on-device model updates without raw data leaving users' phones.
Live quantitative trading system detecting non-statistical anomalies, including mini "black swan" events, in U.S. equities. Full alpha → risk → execution pipeline, custom backtesting engine, and Prometheus/Grafana monitoring. Parallelized live market data streaming and trade execution. Sub-microsecond latencies.
Built a full gas-lifted oil well system simulator from scratch, including a custom oil-gas-water medium and VLP/IPR curve interpolation. Solved the global non-linear optimization problem using ONS. Presented findings at the Wolfram Conference 2023 to an audience of scientists and engineers.
Software optimization of a highly classified algorithm for factoring large primes in tractable time. Required mastering Mathematica and Wolfram Language while developing abstractions that made the system scalable across varied applications.
Designed a personalized dosing system for PRP and bone marrow injections in a largely unregulated space. Used ONS to cluster patients by signal similarity, extracted non-statistical anomalies via DSP, and built an optimization algorithm to recommend optimal viable doses based on baseline patient characteristics.
Co-leading the second Jump Partners vertical, an AI-first search optimization product targeting businesses that need visibility in generative AI responses. Full technical build-out: site analysis engine, reporting pipeline, and client dashboard. Phase 1 live at xeolabs.ai.
Technical depth
across the stack.
- Python
- C++
- Rust
- TypeScript / JavaScript
- Mathematica / Wolfram
- MATLAB
- Modelica
- Go
- Kubernetes / EKS
- Docker
- Apache Kafka
- Apache Flink
- PostgreSQL
- AWS (EKS, S3, CloudFront)
- Firebase
- Prometheus / Grafana
- Federated Learning
- Digital Signal Processing
- Optimization Theory
- Financial Mathematics
- Non-linear Optimization
- Nash Equilibrium AI
- HFT Architecture
- React Native
- React / Vite
- System Architecture
- Cloud-native Design
- Real-time Streaming
- Backtesting Engines
- API Design
Recognition &
milestones.
Delivered a 30-minute technical presentation on gas-lifted petroleum well simulation, covering the physics model, automated generation of custom well systems, and ONS-based global optimization. Presented to scientists and engineers from across the Wolfram research community.
Completed a four-year computer science degree in three years while working a technical internship, founding JDUB Digital, and playing Division I collegiate soccer. Graduated May 2023.
Competed as a Division I collegiate soccer player at USF while simultaneously managing a full technical workload, running a business, and beginning my career in AI. A formative lesson in managing intensity across multiple fronts.
At 24, co-founder and CTO of a holding company with two live AI products, 200+ users, institutional investor attention, and a SOC 2 Type 2 certification in progress. The pipeline of what comes next is the most interesting part.
Let's build.
If you are working on a genuinely difficult technical problem in AI, finance, infrastructure, or anything in between, I would like to hear about it.