Forward Deployed Engineer - Physical AI Cloud Platform

Details

Nebius is building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment. The Forward Deployed Engineer, Cloud Platform is a senior, high-autonomy individual contributor role embedded with strategic customers and ISV partners to ship production infrastructure for real physical AI workloads. This role focuses on making the platform fast, reliable, scalable, secure, and cost-effective, and feeds field learnings into the Nebius Physical AI roadmap.

You may work remotely from the United States (SF Bay Area, CA or Austin, TX preferred).

Responsibilities

• End-to-end ownership inside strategic accounts: discovery, technical scoping, infrastructure design, build, and production rollout for design partners and ISV engagements.
• Build and operate cloud infrastructure and compute orchestration for simulation, training, evaluation, inference, and batch workloads at scale.
• Build platform services for job execution, scheduling, retries, observability, logging, secrets, access control, and cost tracking; integrate Nebius cloud services into the product experience.
• Build onboarding infrastructure for pilots (sandbox environments, dataset storage, workflow execution, deployment) to ensure secure, isolated, observable, and reliable early customer workloads.
• Optimize reliability, security, performance, utilization, and cloud cost across application, network, storage, compute, and orchestration layers; debug cross-layer infrastructure issues.
• Partner with Physical AI Systems and Platform & Product FDEs to support GPU-heavy simulation, training, and evaluation pipelines and to expose infrastructure capabilities via APIs/SDKs/product workflows.
• Help define long-term infrastructure architecture for multi-tenant SaaS, enterprise deployments, and high-throughput physical AI workloads.
• Turn repeated customer infrastructure pain into reusable platform capabilities; collaborate with Field CTO, Product, and Engineering to productize patterns.
• Use modern AI coding tools (Claude Code, Codex, Cursor) to increase engineering velocity and compress build timelines.
• Produce reference architectures, solution templates, and technical documentation; maintain structured feedback loops from field to Product and Engineering.

Requirements

• 6+ years of hands-on engineering experience in backend, cloud infrastructure, platform engineering, or SRE, with at least 2 years in a customer-facing or deployment-oriented technical role (Forward Deployed Engineer, founding engineer, technical co-founder, tech lead embedded with customers, or equivalent).
• Experience building distributed systems, job orchestration, compute platforms, internal developer platforms, or ML infrastructure.
• Strong systems/backend programming skills (Python, Go, or similar).
• Fluency in modern AI coding tools (Claude Code, Codex, Cursor) to design, implement, test, debug, and refactor production-quality software quickly.
• Cloud-native toolchain experience: Kubernetes, containers, CI/CD, observability, cloud networking, storage, IAM/RBAC, and infrastructure as code.
• Familiarity with GPU & HPC workloads: batch jobs, training pipelines, inference workloads, or HPC-style compute environments.
• Proven ability to debug infrastructure issues across application, network, storage, compute, and orchestration layers.
• Strong instincts for security, isolation, RBAC, uptime, and traceability for customer-touching workloads.
• High agency and strong written/verbal communication: able to navigate ambiguity, communicate with customer CTOs, and debrief engagements to leadership.

Nice to have

• Prior experience as a Forward Deployed Engineer or equivalent customer-embedded engineering function.
• Experience with Nebius, AWS, GCP, Azure, Lambda Labs, or other AI cloud infrastructure.
• Experience with Slurm, Soperator, Kubernetes GPU scheduling, Ray, Argo, Airflow, Metaflow, or similar orchestration tools.
• Experience with ML training infrastructure, model serving, simulation workloads, or large-scale data pipelines.
• Experience supporting enterprise customers, design partners, or production pilots.
• Familiarity with NVIDIA GPU infrastructure, CUDA workloads, Isaac Sim, Omniverse, or simulation-at-scale.

Benefits

• Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) plan: up to 4% company match with immediate vesting.
• Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote work reimbursement: up to $85/month for mobile and internet.
• Company-paid short-term, long-term, and life insurance coverage.
• Competitive compensation, career growth, flexibility, ownership, and opportunity to work on impactful AI projects in an international environment.

Pay Transparency

Base compensation range: $179,500 — $224,300 USD

Additional information

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