You will own the end-to-end product roadmap, synthesizing complex problem spaces into clear directions that drive measurable business impact. Additionally, you will engage directly with customers to uncover growth opportunities and partner with engineering teams to ship technical solutions.
You will lead technical implementations for enterprise customers across Latin America, managing the full lifecycle from data discovery to production deployment. Additionally, you will architect semantic definitions and build data pipelines to ensure high-fidelity business insights for AI-driven growth models.
You will build and manage talent pipelines across LATAM, proactively sourcing candidates for diverse roles including engineering, AI, and GTM. You will partner with hiring managers to refine search strategies, conduct screenings, and manage the full candidate lifecycle to ensure high-quality hires.
You will design and implement agentic workflows and evaluation systems to ensure robust performance in production environments. Additionally, you will own the end-to-end lifecycle of AI systems, from experimentation and testing to monitoring and production maintenance.
Identify and define your own role within the company by solving critical business problems or building new functions. Collaborate across disciplines to drive growth and contribute to the development of an AI-native infrastructure.
You will build and own an enterprise sales pipeline from the ground up, identifying key accounts and verticals to drive market presence. You will manage the full sales cycle, navigating complex stakeholder environments to translate technical AI capabilities into measurable business outcomes.
Build and scale the Hilbert AI Portal, focusing on the interactive interface and backend logic for AI agents. Develop enterprise-grade customization logic and internal tooling to monitor and debug ML models.
Architect and implement data integration bridges between customer warehouses and Hilbert's AI growth engine. You will build semantic layers and canonical models to ensure AI agents have a high-fidelity view of business data.
