Senior Technical Project Manager – Applied AI
About The Position
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. Role As a Technical Project Manager for Applied AI in Token Factory, your primary focus will be coordinating complex cross-functional projects, including new region launches, engineering quality and platform-wide improvement projects, and the end-to-end delivery pipeline for new AI models. You will bring together multiple engineering teams, understand the critical path, proactively manage dependencies and risks, and ensure that ambitious technical goals are delivered predictably, on time, and without unnecessary operational overhead.
Requirements
- Excellent project management and delivery skills with the ability to break down ambiguous initiatives into executable plans
- Ability to identify critical paths, manage complex dependency graphs, and coordinate multiple parallel workstreams
- Strong risk management and prioritization skills, with the ability to make progress in fast-changing environments
- Excellent written and verbal communication skills in English
- Comfortable leading incident coordination, facilitating discussions, documenting decisions, and driving follow-up actions
- Strong technical background that allows you to understand engineering discussions, infrastructure dependencies, and architectural trade-offs without being the primary implementer
Nice To Haves
- Experience working with GPU infrastructure, AI/ML platforms, or large-scale inference systems
- Experience delivering cloud infrastructure or data center deployment projects
- Familiarity with capacity planning, production operations, and reliability engineering
- Previous experience in high-growth infrastructure or platform engineering organizations where priorities change quickly and execution speed matters
Responsibilities
- Leading infrastructure and capacity delivery projects, including new region deployments, capacity expansion, or maintenance framework initiatives.
- Coordinating model onboarding and production delivery, from infrastructure readiness to successful customer availability.
- Building and maintaining execution plans, identifying risks early, and ensuring blockers are resolved before they impact delivery.
- Working closely with engineering managers, technical leads, product managers, SRE, infrastructure, networking, security, and other platform teams.
- Facilitating technical decision-making and ensuring ownership and accountability across complex cross-team projects.
- Continuously improving engineering delivery processes to make execution more predictable while maintaining a sustainable pace for engineering teams.
Benefits
- Competitive compensation
- Career growth and learning opportunities
- Flexibility and ownership
- Collaborative and innovative culture
- Opportunity to work on impactful AI projects
- International environment and talented teams
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
