Field CTO, Financial Services AI Infrastructure

Details

Nebius is building a full-stack AI cloud platform for developers and enterprises, supporting workloads from data and model training through production deployment. The platform covers GPU orchestration, inference optimization, compute, storage, networking, and applied AI.

Nebius is seeking a Field CTO for Financial Services to lead the technical side of its financial services vertical. This senior technical leadership role covers architecture discussions with CTOs and heads of research infrastructure, regulated-buyer diligence, reference architectures for financial workloads, and product requirements derived from customer engagements.

The role is initially a hands-on individual contributor position, with a path to building and leading forward-deployed engineers as the vertical grows. The position can be performed remotely from the United States, with New York City preferred. Travel expectations are 10% to 20% for customer visits, executive meetings, and industry events.

Responsibilities

• 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 quantitative and machine learning platforms, and CIOs.
• Partner with Sales leadership on strategic financial services deals, including workload-level cost comparisons against on-premises and hyperscaler options.
• Work with Security, GRC, and Legal on regulated-buyer diligence, including SOC 2 Type II, ISO 27001, DORA alignment, data residency, tenant isolation, key management, audit logging, resilience evidence, concentration risk, and exit and portability plans.
• Define reference architectures for 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.
• Translate customer and account insights into prioritized requirements for Product, Engineering, and Infrastructure teams.
• Create technical narratives, reference architectures, and training materials for field solution architects and sellers.
• Partner with ecosystem vendors, including market and reference data providers, model risk and AI governance tooling providers, trading and risk platforms, and systems integrators.
• Identify integration opportunities and evaluate potential technical M&A targets.
• Build and lead forward-deployed engineers as the financial services vertical grows.

Requirements

• 10+ years of experience in cloud infrastructure, platform engineering, distributed systems, or a closely related technical domain.
• 5+ years of experience in AI, machine learning, or MLOps, with exposure to production or large-scale systems.
• Previous senior technical leadership experience, such as Field CTO, CTO, technical co-founder of a fintech or AI-native company, head of quantitative or machine learning platforms, or principal-level architect on a cloud vendor financial services team.
• Ability to explain distributed systems to engineers and communicate their value and risk profile to CIOs and Chief Risk Officers.
• Experience partnering with Sales to close large enterprise deals and enable field teams with technical assets.
• Experience defining requirements from field evidence and shaping platform strategy.
• Expert-level, production-grade knowledge of GPU architectures, Kubernetes, Slurm orchestration including Soperator, high-performance and parallel file systems, and InfiniBand and Ethernet networking constraints.
• Understanding of model serving, including batch sizes, quantization, KV caching, and latency tradeoffs, with the ability to architect for both high throughput and latency-sensitive workloads such as real-time risk and fraud scoring.
• First-hand experience in capital markets and quantitative research infrastructure, bank or insurer AI platforms, AI-native fintech, or a financial services technical role at a cloud or GPU provider.
• Working knowledge of regulated-vendor reviews, including data residency, third-party and concentration risk, and model risk management expectations such as SR 11-7 in the United States.
• Builder mentality and willingness to start as a hands-on individual contributor.
• Public technical credibility through conference talks, writing, or open-source work.
• Strong executive presence and communication skills.
• Experience operating in fast-moving environments such as hyperscalers, cloud platforms, or advanced AI startups.

Preferred Qualifications

• Hands-on experience with quantitative research infrastructure, low-latency trading systems, or model risk management in a regulated institution.
• Familiarity with hybrid and on-premises GPU environments used by financial institutions.
• Ability to distinguish between customers needing raw cluster access and those needing managed endpoints, and to recommend the appropriate solution.

Benefits

• Base compensation range of $210,000–$260,000 USD.
• 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan with up to a 4% company match and immediate vesting.
• 20 weeks of paid parental leave for primary caregivers and 12 weeks for secondary caregivers.
• Remote work reimbursement of up to $85 per month for mobile and internet.
• Company-paid short-term disability, long-term disability, and life insurance.
• Career growth and learning opportunities.
• Flexible work, ownership, and the opportunity to work on impactful AI projects.

Nebius is an equal opportunity employer. Applicants must be authorized to work in the country in which they apply and must provide proof of employment eligibility as a condition of hire.