Field CTO, Financial Services AI Infrastructure

Nebius

8d•$210,000 - $260,000•Remote

About The Position

Nebius is hiring a Field CTO to lead the technical side of its Financial Services vertical, helping financial institutions run AI workloads in production on Nebius’s specialized AI cloud. The role sits at the intersection of production GPU infrastructure and regulated financial services, and involves engaging with both customers that buy GPU capacity directly and institutions that require extensive security, risk, data-residency, and governance review. The Field CTO will serve as a senior technical leader and the technical face of Nebius to customers, partners, and ecosystem stakeholders. The role covers customer architecture discussions, regulated-buyer diligence, reference architectures for financial workloads, strategic deal support, technical field enablement, and turning customer evidence into product requirements. The position begins as a hands-on individual-contributor role, with a path to building and leading forward deployed engineers as the vertical grows. The role may be performed remotely from the United States, with New York City preferred. Travel is expected to be 10%–20% for customer visits, executive meetings, and key industry events. Base compensation is $210,000–$260,000 USD. Nebius describes its workplace as fast-moving, growth-oriented, collaborative, and focused on meaningful impact, trust, and ownership.

Requirements

At least 10 years of experience in cloud infrastructure, platform engineering, distributed systems, or a closely related technical domain, including at least 5 years in AI, ML, or MLOps with exposure to production or large-scale systems.
Prior senior technical leadership experience, such as Field CTO, CTO or technical co-founder of a fintech or AI-native company, head of a quantitative or ML platform, or principal-level architect on a cloud vendor financial services team.
Ability to explain distributed-system designs to engineers and communicate their value and risk profile to CIOs or Chief Risk Officers.
Experience partnering with Sales to close large enterprise deals and enabling field teams with technical assets.
Experience defining requirements from field evidence and shaping platform strategy; able to explain when a customer request would create technical debt and propose an alternative.
Expert-level, production-grade knowledge of GPU architectures; Kubernetes and Slurm orchestration, including Soperator; high-performance and parallel file systems; and InfiniBand and Ethernet networking constraints.
Understanding of model-serving optimization, including batch sizes, quantization, KV caching, and latency tradeoffs, with ability to architect for both throughput and latency-sensitive needs such as real-time risk and fraud scoring.
First-hand experience in at least one of 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 US SR 11-7.
Independent, hands-on builder mentality, with a point of view on the future of AI infrastructure in financial institutions and willingness to grow a team from an individual-contributor role.
Public technical work, such as conference talks, writing, or open-source contributions, demonstrating credibility with engineering and executive audiences.
Strong executive presence and communication skills, with the ability to influence product teams and leadership through clarity and credibility.
Experience operating in fast-moving environments where requirements evolve, such as hyperscalers, cloud platforms, or advanced AI startups.

Nice To Haves

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 customers who need raw cluster access from those who need managed endpoints and prescribe the appropriate approach.

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 ML platforms, and CIOs; demonstrate performance on customer workloads and explain how architectures fit institutional control frameworks.
Partner with Sales leadership on strategic financial services deals, including workload-level cost comparisons with on-premises and hyperscaler options.
Work with Security, GRC, and Legal to address regulated-buyer diligence, including data residency, tenant isolation, key management, audit logging, resilience evidence, concentration risk, and exit and portability plans; identify gaps and bring them to Product as requirements.
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 evidence into prioritized requirements for Product, Engineering, and Infrastructure teams, and maintain a structured feedback loop with R&D.
Create technical narratives, reference architectures, and training materials to help Field SAs and sellers engage financial services buyers credibly.
Partner with ecosystem vendors, including market and reference data providers, model risk and AI governance tooling, trading and risk platforms, and systems integrators, to identify integration opportunities and evaluate potential technical M&A targets.
Build and lead forward deployed engineers as the vertical grows, defining how they scope and deliver work and share learnings with Product.

Benefits

100% company-paid medical, dental, and vision coverage for employees and families.
401(k) plan with up to 4% company match and immediate vesting.
Paid parental leave: 20 weeks 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 coverage.
Competitive compensation and benefits packages.
Career growth and learning opportunities.
Flexibility and ownership.
Collaborative and innovative culture.
Opportunity to work on impactful AI projects.
International environment and talented teams.