Field CTO, Financial Services AI Infrastructure

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.

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

Nebius is building the AI infrastructure that financial institutions will run AI on in production, from quantitative research and real-time risk to agentic workflows in banks and insurers.

The Field CTO for Financial Services is a senior technical leadership role at the intersection of production GPU infrastructure and the regulated business of financial services. You will lead the technical side of the vertical: the architecture conversation with CTOs and heads of research infrastructure, the technical content of regulated-buyer diligence, the reference architectures for financial workloads, and the product requirements that come out of the field.

Financial institutions buy AI infrastructure differently from most customers. Quantitative funds and AI-native fintechs buy GPU capacity directly and judge it on price-performance, availability, and how the cluster behaves under their own workloads. Banks and insurers add a second review: security, third-party risk, data residency, and exit planning are assessed before a deal reaches architecture discussions. You will earn the trust of both kinds of buyer and help make Nebius an approved supplier to financial institutions.

You will work alongside the Head of Financial Services, Sales, Security and GRC, Product, and Engineering.

The role

begins as a hands-on individual contributor, with a clear path to building and leading forward deployed engineers as the vertical scales.

This is a ground-floor opportunity to define how financial institutions run AI in production on a specialized AI cloud.

You are welcome to work remotely from the United States (New York City preferred). Travel expectations are 10% to 20% for customer visits, executive meetings, and key industry events.

Your responsibilities will include:

• Executive Technical Leadership: Serve as the technical face of Nebius to financial services customers, partners, and ecosystem stakeholders. Lead architecture workshops and technical discovery with CTOs, heads of quant and ML platforms, and CIOs, showing technical buyers how Nebius performs on their own workloads and institutions how the architecture fits their control framework.

• Lighthouse Deal Support: Partner with Sales leadership on strategic financial services deals, including workload-level cost comparisons against on-premises and hyperscaler options.

• Regulated-Buyer Diligence: Work with Security, GRC, and Legal to turn our SOC 2 Type II and ISO 27001 certifications, and our alignment with frameworks such as DORA, into answers that third-party risk teams accept. Cover data residency, tenant isolation, key management, audit logging, resilience evidence, concentration risk, and exit and portability plans. Flag gaps early and bring them to Product as requirements.

• Architectural Guidance: Define reference architectures for financial workloads: quantitative research and backtesting, real-time risk and fraud inference, LLM and agentic workflows in KYC, AML, and document processing, and fine-tuning on sensitive proprietary data.

• Technical Product Strategy: Translate what you learn in accounts into prioritized, evidence-backed requirements for Product, Engineering, and Infrastructure teams, and keep a structured feedback loop so R&D can act on them.

• Field Enablement: Act as a force multiplier for the sales organization by creating the technical narrative, reference architectures, and training materials that help Field SAs and sellers engage financial services buyers credibly.

• Ecosystem & M&A: Partner with ecosystem vendors (market and reference data providers, model risk and AI governance tooling, trading and risk platforms, systems integrators) to identify integration opportunities and evaluate potential technical M&A targets.

• Team Building: Build and lead forward deployed engineers as the vertical grows, setting how they scope, deliver, and hand learnings back to Product.

We expect you to have:

• 10+ years of experience in cloud infrastructure, platform engineering, distributed systems, or a closely related technical domain, including 5+ years in AI, ML, or MLOps with exposure to production or large-scale systems.

• Prior experience in a senior technical leadership role, for example Field CTO, CTO or technical co-founder of a fintech or AI-native company, head of quant or ML platform, or principal-level architect on a cloud vendor financial services team.

• Dual Competency: You can draw a distributed system on a whiteboard for engineers and