About.
Mechanical engineer working across motorsport powertrains and energy storage. Now applying frontier AI to the way these systems are engineered — with a parallel focus on agents and tooling that compress engineering cycles. Currently in Brixworth, UK.
Santiago Isaza is a mechanical engineer focused on motorsport powertrains and energy storage. Current work sits at the meeting point of these systems and frontier AI — applying large models to powertrain testing and validation workflows, building tooling that accelerates engineering cycles, and developing AI agents that take on discrete engineering tasks end-to-end.
The portfolio on this site collects fifteen projects spanning vehicle structures, battery systems, charging electronics, harness methodologies, and AI-driven engineering workflows. The work is presented as explanations rather than promotional copy: each project page describes what was built, how it was structured, how it works, and what was learned. Where confidentiality applies, the corresponding pages stay intentionally high-level and public-domain.
Trained as a mechanical engineer at EAFIT University in Medellín (2017–2022), with a Charging System Engineer dissertation on the EAFIT KRATOS solar car — PCB design under the SAE J1772 protocol, an Arduino state machine integrating Orion BMS and ELCON TC charger, modal and structural verification of the rectifier brackets, all validated under a 24-hour race at the iLumen European Solar Challenge 2022.
A Motorsport & E-Racing master's at QEV Technologies / University of Vic in Barcelona (2022–2023) overlapped with a harness engineering role at Bold Valuable Tech, where the deliverable was a methodology for designing aerospace BMS / BCU wiring harness prototypes in 3DEXPERIENCE / CATIA V6.
Since September 2023 the work has lived inside Mercedes-AMG High Performance Powertrains in Brixworth, UK — first Performance Development (limit calculation through BIPO, rig and dyno testing of full F1 powertrains and subsystems including e-motors, inverters and HV batteries), then Systems Engineering (Simulink modelling of heater behaviour across state of charge, battery temperature and driving cycles, with track-to-simulation correlation for race strategy), and currently Sub System Validation for the 2026 powertrain — pass-fail limits, structure pass-offs, and Test Request leadership across cell pack, inverter and ESME.
What the portfolio now centres on is AI inside that powertrain engineering loop: a Claude Code–driven post-processing repository for the 2026 powertrain, frontier-model–assisted functions that rank subsystems by heat rejection and compute capacity / internal and busbar resistance, and routines that verify inverter sensor gains and offsets without human intervention. Outside Mercedes the same thread runs through personal projects — an agentic PCB design tool driving KiCad through its SWIG API, an autonomous F1 content pipeline running daily on Veo 3 and Remotion, an LLM-maintained engineering wiki, and infrastructure for delegating cheap inference to a remote GPU.
The fastest route is the contact form, which delivers messages directly. The CV below mirrors the portfolio in PDF form for easier sharing with recruiters and hiring managers.
Download CV