N

Nebius

Runs GPU clouds for AI training and deployment

Head of Sales Engineering - Token Factory

Full-TimeUpdated on 10/23/2026
$228k - $285k
Expert
Remote in USA
RemoteRemote work is available from the United States.
Solution EngineeringPre-Sales Solution Engineering

About the job

Requirements
  • Deep understanding of AI inference systems and GPU-backed infrastructure.
  • Significant experience with large language model workloads and performance-sensitive environments.
  • Experience with inference frameworks and libraries such as vLLM, SGLang, and TensorRT-LLM.
  • 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.
  • Judgment around when to standardize, customize, or decline requests.
  • Ability to challenge assumptions and push back constructively with customers and internal stakeholders.
  • Commercial awareness, including understanding engineering time and GPU capacity as 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.
Responsibilities
  • Lead, coach, and develop a high-performing team of Sales Engineers.
  • Set clear expectations for technical quality, customer engagement, and commercial impact.
  • Provide hands-on technical mentorship and support individual team members' growth.
  • Establish consistent approaches to discovery, architecture reviews, proof-of-concept qualification, and production readiness.
  • Allocate Sales Engineering capacity across opportunities based on strategic value, technical complexity, and probability of success.
  • Create an environment where the team can challenge assumptions, escalate risks early, and make high-quality technical decisions.
  • Support hiring, onboarding, and development of the Sales Engineering organization as the business scales.
  • Act as the senior technical advisor on strategic and complex customer opportunities.
  • Lead deep technical discovery with engineering teams, technical founders, and customer executives.
  • Guide the team in understanding model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies.
  • Translate customer ambition into production-feasible architectures.
  • Identify hidden technical, operational, and economic risks before significant resources are committed.
  • Step into critical opportunities when additional technical depth or leadership is required.
  • Partner with Sales leadership on strategic deals, account planning, and technical qualification.
  • Influence deal strategy through architectural clarity and understanding customer requirements.
  • Establish technical qualification and escalation mechanisms for complex opportunities.
  • Ensure customer commitments align with current or strategically planned platform capabilities.
  • Prevent misaligned commitments before Engineering resources are allocated.
  • Improve proof-of-concept-to-production conversion by ensuring technical and economic realism from the beginning.
  • Help Sales and Sales Engineering balance customer urgency with sustainable platform development.
  • Establish standards for how the team scopes, designs, and evaluates customer proof-of-concepts.
  • Ensure measurable success criteria are defined, including latency, time to first token, throughput, reliability, and cost envelope.
  • Guide workload classification and determine the appropriate depth of optimization.
  • Align resources across Sales Engineering, ML Solution Architecture, Product, Engineering, and GPU capacity.
  • Drive structured go/no-go decisions for complex engagements.
  • Prevent uncontrolled customization, hidden research and development, and poorly scoped engineering commitments.
  • Ensure successful proof-of-concepts have a clear and realistic path to production.
  • Build a systematic view of technical patterns emerging across customer engagements.
  • Identify recurring workload, configuration, and architecture patterns.
  • Quantify demand for advanced optimizations such as quantization, speculative decoding, and other inference techniques.
  • Surface structured customer insights and technical evidence to Product and Engineering leadership.
  • Distinguish repeatable platform requirements from one-off customer requests.
  • Influence platform priorities based on real workload data and commercial opportunity.
  • Turn successful customer architectures and lessons learned into reusable patterns for the Sales Engineering organization.
  • Serve as a key interface between Sales, Sales Engineering, Product, and Engineering.
  • Represent customer technical requirements while maintaining a clear view of platform strategy and engineering constraints.
  • Improve how technical decisions, risks, and dependencies are communicated across teams.
  • Establish feedback loops so Product and Engineering understand emerging customer demand.
  • Help leadership make informed tradeoffs between revenue opportunity, customer impact, and engineering investment.

About the company

Nebius runs an AI cloud for developers, researchers, and enterprises that train models and put them into production. Its AI Cloud combines GPU computing, storage, networking, and managed services, while Token Factory runs models through an API so teams do not manage the underlying servers. Customers rent computing and storage at usage rates or reserve capacity, choosing resources that fit short experiments or sustained production workloads. Beyond the cloud, the group owns Avride, which develops autonomous vehicles and delivery robots, and TripleTen, which teaches technical skills for people changing careers. The publicly listed group is headquartered in Amsterdam, Netherlands.

Company Size

1,001-5,000

Company Stage

IPO

Headquarters

Amsterdam, Netherlands

Founded

1997

Get referred to Nebius

See people who can refer or advise you

Simplify Jobs

Simplify's Take

What believers are saying

  • Parent sales are expanding: August 2026 results showed quarterly group revenue rising 454% to $582.3 million.
  • Enterprise distribution gains a channel: September 2026's Palantir partnership names Nebius its preferred sovereign AI infrastructure partner.
  • Junior engineers get guided production experience: Early Talent participants work on real products with dedicated experienced buddies.

What critics are saying

  • Existing shareholders faced dilution: August 2026 financing exchanged $800 million of older debt for approximately 15.8 million shares.
  • Remote flexibility is limited: its careers FAQ usually permits only one or two home working days each week.
  • Expansion still loses money: August 2026 results recorded a $175.9 million quarterly group operating loss.

What makes Nebius unique

  • Hardware and software share one design: Nebius engineers its servers, racks, cooling, and cloud platform together.
  • Computing heats nearby homes: its Finnish data center feeds recovered heat into the local district heating network.
  • Its engineers started together: the founding team brought years of shared big-tech infrastructure work into Nebius.

Help us improve and share your feedback! Did you find this helpful?

Benefits

  • Health Insurance
  • 401(k) Company Match
  • Parental Leave
  • Remote Work Options
  • Disability Insurance
  • Life Insurance
  • Hybrid Work Options
  • Professional Development Budget

Growth & Insights and Company News

Headcount

6 month growth

5%

1 year growth

-1%

2 year growth

-3%
Yahoo Finance
Oct 22nd, 2026
Neoclouds explained: GPU providers behind the AI boom face a $3.5T impairment risk

Neoclouds, specialist providers that rent out GPU capacity for AI training and inference, have gone from unknown startups to listed companies with contracts worth billions of dollars. CoreWeave, Nebius and IREN lead the listed group; Lambda, Crusoe and Fluidstack remain private. Their shares fell hard in October 2026. CoreWeave dropped 29%, leaving it valued at about $34 billion against a 2025 peak of about $90 billion; Nebius fell 27% and IREN 32%. CoreWeave's unsecured debt yielded about 15%. On October 14, 2026, Gartner predicted that more than 80% of neocloud providers will stop operating independently by 2030. It also warned that more than $3.5 trillion of AI infrastructure spending could face impairment. Demand remains strong. CoreWeave co-founder Brannin McBee said nearly all of its 2027 capacity is sold.

BBX
Oct 22nd, 2026
Nebius secures $3.5B Citibank financing for global AI cloud expansion

Nebius Group, an AI cloud service provider, has secured a $3.5 billion priority secured financing line from Citibank. The company will use the funds to support the global expansion of its AI cloud computing business.

Business Wire
Oct 21st, 2026
Nebius launches public live GPU spot pricing and adds $10M in grants for Europe's AI builders

Nebius (Nasdaq: NBIS), the AI cloud company, has launched public live spot pricing for GPU compute, giving teams more visibility and control over costs. Prices are available at nebius.com/spot-prices and on Shadeform, Silicon Data, and GPU Finder. The company is also offering reserve auctions for short-term capacity blocks and pay-as-you-go access. It is piloting a rebate programme that lets customers return idle GPUs to the spot pool. Nebius runs capacity in Finland, France, the UK, Spain, Estonia, and Iceland. Customers include Black Forest Labs, Photoroom, Prosus, and bunq. The Nebius AI Builder Program is expanding across Europe with an additional $10 million in compute grants.

CNBC
Oct 21st, 2026
Nebius says AI computing prices are rising faster than expected as investors question neocloud model

Nebius is seeing AI computing prices rise faster than expected, chief revenue officer Marc Boroditsky told CNBC on Wednesday. The view comes as investors question the neocloud business model after CoreWeave's borrowing costs spiked. Boroditsky said Nebius does not carry CoreWeave's level of debt. An auction for computing capacity on Tuesday showed continued rises in price per megawatt, he said, and 2027 capacity would sell out if brought online. Crusoe chief executive officer Chase Lochmiller also reported higher prices for older Nvidia chips than when they were first deployed. Nebius shares rose after SpaceX said revenue at its AI business jumped ninefold to $7.56 billion.

Yahoo Finance
Oct 21st, 2026
Musk calls AI capacity glut talk "ridiculous", lifting CoreWeave and Nebius after SpaceX's $14.58B quarter

Elon Musk lifted neocloud stocks a week after hurting them, saying talk of excess AI infrastructure capacity is "ridiculous." He spoke on SpaceX's earnings call late Tuesday. "I do not think we are going to have a demand issue here," Musk said. He added that a six-month payback period for compute next year is not impossible. Last week, Musk replied "Yikes" on X to a post about rising yields on CoreWeave's bonds, which helped fuel a sell-off in CoreWeave and Nebius shares. In pre-market trading Wednesday, CoreWeave and Nebius each gained 2%, and IREN rose 3%. SpaceX's third-quarter revenue was $14.58 billion, up 161% year over year and above analyst estimates of $12.7 billion. Earnings per share were $0.35, $0.20 ahead of forecasts.