Technical Director, Media & Entertainment AI Infrastructure

The role

The Technical Director of Media and Entertainment, AI Infrastructure is a senior engineering leader who will initially operate as an individual contributor at the intersection of deep AI infrastructure engineering and the business of media and entertainment, with a clear path to building and leading a team as the business scales.

You will work alongside CTOs and engineering leaders at studio groups, VFX houses, gaming studios, agency holding companies, and generative AI model companies. Your role is not to pitch them; it is to build with them. You will translate their most complex infrastructure problems into engineered solutions, own the technical relationship with our most strategic ISV and cloud-native partners, and use what you learn in the field to directly influence the M&E product roadmap alongside Nebius's global Head of Product and Head of Engineering.

This is a ground-floor opportunity to define what AI-native infrastructure looks like for an industry in the middle of a fundamental transformation.

You are welcome to work remotely from the United States (SF Bay Area or NYC preferred) Travel expectations 10%-20% for executive meetings and key industry events.

Your responsibilities will include:

AI Infrastructure Architecture

• Own the Technical Blueprint: Personally architect the infrastructure solutions for our most strategic M&E partnerships, studio-scale content production pipelines, agency data consolidation plays, generative AI model deployments. These architectures must be engineered to survive real-world scale, not just pass a POC.
• The Physics to P&L Narrative: Fluently demonstrate to executive stakeholders how infrastructure decisions, data lake locality, storage tiering, inference optimization, directly impact their business model and operability.

Forensic Requirement Gathering

• Deconstruct the Bottleneck: Go beyond the stated problem to find the technical truth. Translate vague business goals (e.g., “We need lower rendering costs”) into precise engineering requirements (e.g., “We need to optimize the inference batch size on L40s to reduce cost-per-token by 30%”).
• Map the Transition: Identify exactly where a customer sits on the curve from legacy service bureau to AI-native tech platform and prescribe the specific infrastructure intervention needed to move them forward.

ISV & Partner Technical Strategy

• Build and Validate the Integration Layer: Identify, engage, and technically validate relationships with the most critical ISVs in the media and entertainment ecosystem.