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Lead multidisciplinary technical due diligence for powered land and build-to-suit AI infrastructure across the Americas. Define and manage scopes, procure and oversee consultants, interpret technical studies (geotechnical, environmental, utilities, network), quantify risks, recommend mitigations, and present findings to support acquisition and development decisions. Build repeatable standards, playbooks, and consultant networks.

The Enterprise Technical Architect will lead the architecture strategy for GTM systems, focusing on CRM, AI integration, and enterprise platforms. Responsibilities include designing scalable architectures, defining integration strategies, and ensuring system governance and modernization.

Own named enterprise accounts in priority verticals to sell Nebius GPU-native cloud infrastructure. Drive complex, multi-stakeholder deals, co-sell with NVIDIA/OEMs/SIs, navigate regulated buying cycles, build executive relationships, manage pipeline to quota, and expand multi-year AI training and inference deployments.

Lead and scale a Forward Deployed Engineering organization supporting AI customers: hire and coach FDEs, define operating models and technical standards, engage executives and partners, convert field learnings into reusable platform improvements, and represent the function in product and ecosystem strategy.

Drive adoption of Nebius AI and cloud solutions by generating leads, building enterprise relationships, crafting solution proposals with technical teams, negotiating contracts with C-suite buyers, and closing deals to meet revenue targets. Collaborate cross-functionally and stay current on industry trends to position offerings effectively.

Lead and grow strategic MSP and VAR partnerships across the US: develop partner enablement, negotiate contracts, align with sales and leadership, drive business development, analyze partner performance, and travel up to ~25% regionally.

Design, build, and operate reliable backend systems while mentoring engineers, participating in design discussions, and improving system performance.

Work onsite in New York with enterprise customers to design, prototype, and deploy production-grade AI systems using Tavily's API. Build RAG pipelines, agent workflows, integrations, and POCs; drive adoption, monitor usage, and translate customer needs into product and engineering roadmap inputs.

Design, build, and operate a production-grade billing platform for an agentic search API: metering, aggregation, prepaid wallets, subscriptions, enterprise contracts, reconciliation, idempotency, invoicing, migration to a new billing system, observability, and SOX/compliance readiness.

Embedded with strategic customers, own end-to-end design, build, and production rollout of cloud infrastructure for large-scale GPU/HPC AI workloads. Build compute orchestration, platform services, onboarding sandboxes, and reliability/security tooling. Turn field learnings into reusable platform capabilities and partner with Product and Engineering to productize them.