Artificial Intelligence Lead (AI Lead)

Role Overview

Platzi is seeking an AI Lead (Artificial Intelligence Lead) to define how AI shapes its products and internal ways of working. This is a hands-on technical leadership role: you’ll set AI direction across the stack, while also building and shipping production systems (including deciding when to use foundation models vs. building from scratch).

What You’ll Do

• Own Platzi’s AI roadmap, spanning AI infrastructure/tooling and learner-facing features.
• Design, develop, and deploy machine learning models, LLM-powered features, and AI pipelines at production scale.
• Convert ambiguous product/business goals into concrete technical solutions with Product, Engineering, and Data.
• Evaluate and prototype emerging AI approaches with a bias toward shipping, including:
  • Foundation models
  • RAG architectures
  • Agentic frameworks
• Establish engineering practices for:
  • Model evaluation and monitoring
  • Responsible AI use
  • MLOps across the organization
• Mentor and grow a team, promoting rapid but deliberate experimentation and strong technical judgment.
• Stay current with AI research and identify what’s worth applying to real problems now.
• Communicate AI strategy and technical tradeoffs clearly to non-technical stakeholders, including leadership and external partners.

Requirements

• 7+ years experience in machine learning, applied AI, or related fields, including 2+ years in a technical leadership/staff-level role.
• Deep hands-on expertise with modern ML frameworks: PyTorch, TensorFlow, or JAX.
• Strong LLM ecosystem skills: fine-tuning, RAG, prompt engineering, vector databases, and agentic frameworks.
• Demonstrated production experience building and deploying AI/ML systems at scale.
• Solid understanding of NLP and deep learning architectures, including retrieval-augmented generation.
• Experience designing MLOps pipelines: model versioning, A/B testing, monitoring, and retraining workflows.
• Ability to lead and grow technical teams with clear technical judgment (minimal process overhead).
• Strong communication: can explain model tradeoffs to engineers and business impact to executives.

Nice to Have

• Experience applying AI in education, content generation, or personalization.
• Open-source contributions or published research.