Lead Sales Engineer – Token Factory

Job not on LinkedIn

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $228k - $285k / year

⏰ Full Time

🟠 Senior

💸 Sales Engineer

👻 Ghost score 20%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Nebius Group

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🤖 Artificial Intelligence

🏢 Enterprise

☁️ SaaS

Artificial Intelligence • Enterprise • SaaS

Nebius Group is building one of the world’s leading AI infrastructure companies, focusing on providing the necessary compute, storage, and tools for developers in the AI space. Based in Europe and listed on Nasdaq, Nebius has a global presence with R&D centers across Europe, North America, and Israel. The company's primary offering is an AI-centric cloud platform designed for intensive AI workloads, complemented by various other businesses involved in generative AI development, edtech, and autonomous technology.

📋 Description

• Lead, coach, and develop a high-performing team of Sales Engineers • Set standards for technical quality, customer engagement, and commercial impact • Establish consistent approaches to discovery, architecture reviews, PoC qualification, and production readiness • Allocate Sales Engineering capacity across strategic opportunities • Support hiring, onboarding, and organizational development • Act as senior technical advisor on strategic and complex customer opportunities • Lead technical discovery with engineering teams, technical founders, and customer executives • Translate customer needs into production-feasible architectures • Identify technical, operational, and economic risks • Partner with Sales leadership on strategic deals, account planning, and technical qualification • Govern technical qualification, escalation, customer commitments, and deal strategy • Improve PoC-to-production conversion • Establish standards and measurable success criteria for customer PoCs, including latency, TTFT, throughput, reliability, and cost • Align resources across Sales Engineering, ML Solution Architecture, Product, Engineering, and GPU capacity • Drive structured Go / No-Go decisions and prevent uncontrolled customization • Identify recurring workload, configuration, and architecture patterns • Quantify demand for quantization, speculative decoding, and other inference techniques • Surface customer insights to Product and Engineering leadership • Influence platform priorities using workload data and commercial opportunity • Serve as an interface between Sales, Sales Engineering, Product, and Engineering • Improve communication of technical decisions, risks, and dependencies • Help leadership balance revenue opportunity, customer impact, and engineering investment

🎯 Requirements

• Deep understanding of AI inference systems and GPU-backed infrastructure • Significant experience with LLM workloads and performance-sensitive environments • Experience with inference frameworks and libraries such as vLLM, SGLang, and TensorRT-LLM • Strong ability to reason about latency, throughput, GPU utilization, cost, and architecture tradeoffs • Experience leading, mentoring, or managing Sales Engineers, Solution Architects, or similar customer-facing technical teams • Demonstrated success supporting complex enterprise or developer-focused technical sales cycles • Strong customer presence with engineering-first organizations • Ability to operate credibly with technical founders, engineering leaders, and senior customer stakeholders • Strong judgment around when to standardize, when to customize, and when to say no • Comfort challenging assumptions and pushing back constructively with both customers and internal stakeholders • Commercial awareness – understanding that engineering time and GPU capacity are strategic resources • Ability to move between detailed technical discussions, deal strategy, team leadership, and executive communication • Experience building repeatable processes and technical standards in a fast-growing organization • Applicants must be authorized to work in the country in which they apply and provide proof of employment eligibility

🏖️ Benefits

• Competitive compensation • Career growth and learning opportunities • Flexibility and ownership • Collaborative and innovative culture • Opportunity to work on impactful AI projects • International environment and talented teams