Head of AI Engineering

This is a fully remote position, open to applicants in Colombia.

📋 Description

• Take ownership of all engineering deliverables, ensuring quality, scalability, and timely execution.

• Lead and manage the entire engineering team, including AI Engineers, ML Engineers, MLOps, and Data Engineers.

• Implement and oversee Agile/Scrum methodologies, including sprints, backlog grooming, ticketing, and release planning.

• Foster a culture centered on accountability, experimentation, and continuous improvement.

• Define and standardize best practices throughout the entire AI/ML lifecycle, from experimentation to deployment and monitoring.

• Design and manage a comprehensive ML platform focused on infrastructure, scalability, reliability, and rapid iteration.

• Develop scalable, end-to-end ML solutions aimed at predictions, recommendations, search, and growth systems.

• Assess experiments, document results, identify successful strategies, and implement them across the team.

• Actively participate in system architecture and key technical decision-making.

• Supervise model training, optimization, deployment, and performance evaluation.

• Propel data excellence through clean pipelines, robust governance, and actionable insights.

• Create frameworks that incorporate generative AI into engineering workflows.

• Participate in client meetings as a senior technical representative, shaping solutions and building trust with stakeholders.

• Collaborate with product managers and business leaders to convert business objectives into technical roadmaps.

• Clearly present trade-offs to ensure clients understand what is being developed and its impact on their business.

• Recruit, coach, and mentor exceptional AI-focused engineers and engineering leaders.

• Establish defined career paths, feedback mechanisms, and performance benchmarks.

• Expand the AI function across MLE, MLOps, and Data Engineering as the organization scales.

⛳️ Requirements

• Over 10 years of engineering experience with substantial and demonstrated leadership responsibilities.

• Proven experience managing large engineering teams in dynamic, high-accountability settings.

• In-depth knowledge of AI/ML systems, including generative AI, model training, and production deployment.

• Strong proficiency in Agile/Scrum methodologies and the operational discipline necessary for running a high-output engineering organization.

• Experience in architecting and scaling ML platforms and data infrastructure.

• Comfortable in client-facing roles, with the ability to translate complex technical concepts into business value.

• Proficiency in English at a C1 level or higher.

🏝️ Benefits

• Flexible working arrangements.