I turn customer and operational problems into AI integrations, automation, and working tools. My focus is AI solutions engineering: understand the workflow, design the solution, build with AI coding agents, test it, and own its operation.
At JoGo.Team, I build AI capabilities for a sports marketplace. My background in customer success, technical sales, and radio systems helps me connect business needs with implementation and explain the tradeoffs to the people using it.
Open to remote AI Solutions Engineer, AI Solutions Implementation, and AI Automation roles. Connect on LinkedIn.
| Area | Project and evidence | What it demonstrates |
|---|---|---|
| AI + sports marketplace | JoGo MCP case study | Connecting assistants to a real platform through structured tools |
| Customer operations + SaaS | Account intelligence · sample report | Risk prioritization, optional LLM briefs, and customer-facing reporting using synthetic accounts |
| Retention + lifecycle automation | SMS / WhatsApp re-engagement | Engagement scoring and channel selection, with a no-send demonstration |
| Radio + hardware integration | SmartSDR client | Network discovery, device commands, and asynchronous status callbacks |
| Radio + external data | HF propagation checker | Translating space-weather inputs into an explainable band-scoring heuristic |
| AI products + technical demonstrations | Quest demos | Evaluating Figma-to-React output and explaining integration tradeoffs to technical buyers |
The repositories include demonstration code and technical utilities. Each README explains its scope and how to inspect it. Synthetic industry examples are not client references; employer experience does not imply deployment of these public projects at those employers or their customers.
I use an AI-native development process. AI coding agents help produce the code; I own the problem definition, solution design, review, testing, troubleshooting, and completed workflow. Quest's repository explicitly identifies its generated platform output.
- Discover and explain: connect customer requirements to a practical workflow, demonstrate the result, and discuss limitations.
- Integrate: work with MCP, REST APIs, webhooks, messaging services, and operational data.
- Operate and improve: investigate failures, evaluate fallback behavior, and use customer feedback and analytics to guide the next change.
Tools across my work include Claude Code, MCP, Anthropic and OpenAI APIs, Python/Django, Twilio, Stripe Connect, SendGrid, Cloudflare, GitHub Actions, Sentry, GA4, and Google Search Console. The projects above show specific slices of that work, not a claim that every tool is implemented in every repository.
- JoGo.Team: customer operations and AI integration for a sports marketplace.
- BP3 Global: enterprise AI and automation sales across banking and manufacturing.
- Konica Minolta: public-sector accounts, document workflows, and AI security platforms.
- FlexRadio Systems: customer-facing work with software-defined radio across defense, utilities, and emergency response.
- Quest: demonstrations of an AI design-to-code product for enterprise buyers.
- Motorola BGH: hands-on radio and electronics support.
Engineering education at UTN FRBA, Extra Class amateur radio background, and bilingual English / Spanish communication inform how I approach technical problems.