Head of AI Engineering

Engineering Delivery & Leadership:

• Own all engineering deliverables — quality, scalability, and on-time execution
• Lead and manage the full engineering organization: AI Engineers, ML Engineers, MLOps, and Data Engineers
• Establish and run Agile/Scrum processes: sprints, backlog grooming, ticketing, and release planning

AI/ML Strategy & Architecture:

• Define and standardize best practices across the full AI/ML lifecycle — from experimentation through deployment and monitoring
• Architect and oversee a full ML platform: infrastructure, scalability, reliability, and rapid iteration
• Design and build scalable, end-to-end ML solutions for predictions, recommendations, search, and growth systems

Client Engagement:

• Join client calls as a senior technical voice, shaping solutions and building stakeholder trust
• Partner with product managers and business leaders to translate business objectives into technical roadmaps
• Present trade-offs clearly so clients understand what's being built and why it will move their business