Diego Gil

AI Integration & LLM Architecture: Designed and integrated advanced AI solutions using Large Language Models (LLMs) and autonomous Agents. Implemented Retrieval-Augmented Generation (RAG) architectures to enhance data retrieval, automate complex workflows, and deliver intelligent features within the platform.

End-to-End Feature Development: Designed, developed, and deployed robust full-stack features for the core platform, directly improving product functionality and user experience for logistics professionals.

Technical Leadership & Architecture: Spearheaded the design of technical solutions, successfully translating complex business requirements into clear, scalable, and actionable technical architectures during planning phases.

Code Quality & Review: Championed high engineering standards by conducting rigorous code reviews, enforcing best practices, and ensuring a secure, maintainable codebase.

Mentorship & Team Collaboration: Mentored fellow engineers and cross-functional team members, providing technical guidance and fostering a collaborative culture of continuous learning and high performance.

Incident Management & Resolution: Actively monitored system health, quickly troubleshooting and resolving critical production incidents to minimize downtime and ensure seamless financial transactions.

• • Offered experience with Python, Go, TypeScript, Dart, Django, React, Flutter, SQL, AWS, Docker, LangChain, LLMs, RAG, Gemini, GPT.

I led a specialized team focused on internal research projects aimed at teaching AI models how to autonomously navigate computer interfaces. As a Full Stack Engineer and Team Lead, I developed a custom embedded operating system designed to capture user actions linked to complex reasoning, providing essential data for model training. I worked tightly with core AI research teams to iterate on application features and ensure high-fidelity data collection. Beyond coding, I managed a team of direct reports and led data quality initiatives analyzing model shortcomings to strategically guide the creation of targeted datasets that directly improved the AI's performance and capabilities.

Responsibilities

AI Training Infrastructure & Embedded OS: Engineered a custom embedded operating system application designed to collect granular user actions coupled with human reasoning.

Cross-Functional Research Collaboration: Partnered directly with core AI Research and Data Generation teams, rapidly iterating on the application's features to ensure the data collection tools perfectly aligned with evolving model training requirements.

Team Leadership & Project Management: Acted as a Team Lead, managing and mentoring a team of direct reports. Orchestrated project lifecycles, delegated tasks, and guided technical efforts to deliver high-impact research tools on schedule.

Data Quality & Gap Analysis: Conducted rigorous analysis of training data quality and evaluated model performance to identify behavioral shortcomings. Strategically directed the team's data collection efforts to generate targeted datasets that resolved specific model deficiencies.

End-to-End Full Stack Development: Built scalable, performant full-stack architectures for internal tooling, ensuring a seamless and responsive user experience for data annotators and researchers generating complex AI training data.

Backend-Driven Feature Development: Designed, developed, and deployed scalable backend services and APIs for the core AI insurance platform, optimizing data processing, third-party integrations, and automated quote generation.

Technical Architecture & Planning: Led technical planning sessions, successfully translating complex business and product requirements into robust, actionable backend architectures and guiding the engineering team through implementation.

Code Quality & Peer Review: Enforced high engineering standards by conducting rigorous code reviews, optimizing database queries, and ensuring a secure, maintainable, and highly performant backend infrastructure.

Mentorship & Technical Leadership: Acted as a key technical leader, mentoring fellow engineers, providing hands-on guidance, and fostering a collaborative culture of best practices and continuous learning.

Incident Management & System Reliability: Actively monitored server health and application performance, swiftly troubleshooting and resolving critical production incidents to ensure uninterrupted service for dealership partners and customers.

Strategic Problem Solving: Bridged the gap between product managers and the development team during agile ceremonies, leading the design of technical solutions to overcome complex architectural challenges.

• • Offered experience with Python, JavaScript, Type Script, Django, Flask, Fast API, SQL, AWS, CI/CD, and Docker.

• • Developed robust, scalable, modular, and API-centric infrastructures.