I'm Ruben Sanchez, an AI and software systems engineer. I build full-stack products and the systems behind them, from frontend and backend architecture to data pipelines, AI features, model integration, evaluation, and deployment. I take ambiguous technical problems from idea to working system and own the work end to end.
I care more about the problem and the working relationship than the size of the company.
Teams with a working concept, an early frontend, or a rough prototype that needs the rest of the product built around it.
Firms with more client demand than technical capacity, especially when the work is unusual or the turnaround matters.
Owners who need custom software, an integration, or a website that solves a specific operational problem.
Current product engineering, client websites running in production, and selected public research.
Current product work
I work with Consciens as a contractor and core member of the internal team. I am building the database, embedding and retrieval systems, caching, context management, API and MCP routes, and the connection between those systems and the frontend for its Company Brain product.
Publishing / creator platform
A custom author platform for a New Adult fantasy series, with its own visual identity, book and character pages, and a content system the author can update without editing page code.
Local services / wellness
A warm, straightforward website for a sound and yoga practitioner in Colorado Springs, with events, offerings, editorial content, and booking built into the visitor experience.
MODEL ENGINEERING
A reasoning-distillation system that trains small Qwen3 models on genomic variant classification, with verifier-guided data filtering and a full evaluation pipeline.
My best work begins when the idea is clear but the product still has a lot left to build.
LLM features, agents, retrieval, model routing, local models, evaluation, and domain-specific model adaptation, built as parts of a larger system.
Frontend, backend, databases, and product workflows for SaaS, dashboards, and operational tools, designed and built as one system.
Databases, retrieval systems, third-party services, and the routes that connect the pieces reliably.
I take the part that already proves the idea and build the backend, data, integrations, testing, deployment, and documentation around it.
I assess stalled or unstable software, identify what is worth keeping, and create a practical path forward.
Fast, maintainable sites with the booking, payments, content, or custom behavior the business actually needs.
Fast iteration, clear communication, and enough structure for the next person to understand the system.
AI coding tools are part of my everyday workflow. I am up front about that because you should know how your software is being built. I use them for implementation speed while I remain responsible for the architecture, decisions, integration, testing, security, and final result.
Models are components inside software systems, not the whole product. I design the data flow, evaluation, controls, interfaces, and failure handling around them, the same way I engineer any other part of the stack.
Before software, I served as an all-source intelligence analyst in the U.S. Army. That work taught me how to take incomplete, complicated information, find what matters, and explain it clearly to the person making the decision.
Each of my public product builds reached an initial MVP in under a week. I then spent longer hardening them with tests, documentation, security controls, CI, and deployment support. Speed gets the product moving. Follow-through is what makes it dependable.
A defined product milestone, scoped around what needs to work next.
An assessment and stabilization plan for software that is stuck, fragile, or hard to extend.
Continued engineering for teams that need a reliable technical contributor without hiring a full department.
I price each project around its scope and value instead of publishing a generic rate card. I will be candid about what is worth building, what can wait, and how to find a scope that works for both of us.
Each of my three public product builds reached an initial MVP in under a week. That does not mean every client project takes a week. Existing code, integrations, product decisions, and production requirements all affect the timeline. I move quickly, then spend the time needed on testing, security, documentation, and deployment.
Yes. AI tools are part of my normal development process, and I am transparent about that. I use them to move faster while I remain responsible for architecture, implementation decisions, integration, testing, security, debugging, and the final result.
The working software, its source code, and the documentation needed to understand and operate it. Depending on the project, that can include tests, architecture notes, API documentation, CI, deployment instructions, and security decisions.
If you have a prototype, a half-built product, or a system that needs rescuing, a short conversation is enough to see whether I can help.