About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The role  The Field CTO, Media & 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 landscape, from rendering and VFX toolchains to generative AI platforms. • Define the Standard: It is not enough to support these tools. You will define the reference architectures for how they run best on Nebius infrastructure, and work directly with ISV engineering teams to build and publish those standards. • Decide What’s Worth Doing: In partnership with the GM, evaluate ISV and partner opportunities on their technical merit and strategic leverage , and be equally rigorous about what not to pursue. Internal Technical Influence • Shape the M&E Roadmap: Use forensic evidence from the field to prioritize and justify the M&E vertical roadmap. You will work directly with Nebius’s global Head of Product and Head of Engineering to translate partner and customer needs into product direction. • Lead the M&E Product Summit: Chair a quarterly summit with Core Engineering leadership, using field evidence to drive roadmap decisions and maintain vertical momentum. We expect you to have:  • 12+ years of experience in cloud infrastructure, platform engineering, distributed systems, or a closely related technical domain. • Executive Presence: Capable of commanding a room of engineers and presenting a layered technical roadmap to a C-Suite. You have operated at the top-to-top level , your counterparts are CTOs and VPs of Engineering. • Builder Mentality: This role begins as a hands-on individual contributor position. You will architect and ship solutions alongside partners and build the assets (reference architectures, integration playbooks, technical frameworks) that make Nebius's M&E infrastructure strategy defensible and scalable. As the business case develops, this role is explicitly designed to grow into a team-building and leadership function, with the expectation that you will recruit, shape, and run that team. You may have come from a startup, run your own company, or operated within a large org in a way that felt like building from zero, and you know how to transition from maker to multiplier. • Product-Minded: Experience defining a platform strategy, not just executing tickets. You are comfortable telling a customer “No” when a request creates technical debt, and proposing a better alternative. • Ambiguity Tolerance: You thrive in environments where requirements are evolving. You do not wait for a roadmap; you build it. • Forensic Mindset: You are not satisfied with surface-level answers. You dig into the kernel, the logs, and the P&L to find the truth. AI Infrastructure Expertise • Mastery of the Stack: Expert-level, production-grade knowledge of GPU architectures (H100, L40s), Kubernetes orchestration including Soperator, high-performance and parallel file systems (e.g., Lustre, WEKA), data lake architecture, and networking constraints (InfiniBand/Ethernet). • Inference Optimization: You understand the nuances of model serving , batch sizes, quantization, KV caching, latency tradeoffs , and can architect solutions for both massive throughput and real-time (sub-50ms) demands. Domain Context: Media & Entertainment Industry Fluency: You have operated within the M&E ecosystem and can speak to the infrastructure implications across the following sub-sectors: • Gaming • Multimodal Generative Models • AdTech • VFX / Content Production Non-negotiable: Candidates without deep, production-grade working knowledge of GPU infrastructure and inference-based solutioning will not be considered. This is a hard requirement, not a preference. AI Infrastructure Expertise  • Mastery of the Stack: You must be an expert in the physics of AI infrastructure. This includes deep, production-grade knowledge of GPU architectures (H100 vs. L40s), Kubernetes orchestration (K8s), high-performance storage parallel file systems (e.g., Lustre, WEKA), and networking constraints (InfiniBand/Ethernet).  • Inference Optimization: You understand the nuances of model serving—batch sizes, quantization, KV caching, and latency tradeoffs—and can architect solutions for both massive throughput and real-time (sub-50ms) demands.  It will be an added bonus if you have: • Hands-on experience with VFX pipelines, studio-scale content production workflows, or the cloud tooling that powers them , render farm management, distributed simulation, asset pipeline tooling. You understand how content gets made, moved, and transformed at scale, and what infrastructure makes that possible. • Strategic Empathy: The ability to distinguish between customers who need raw bare-metal access and those who need managed…