Best suited to technically proficient leaders with experience in AI infrastructure working in developer-native environments.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Nebius
About Nebius:
Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.
Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.
Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.
The role
We are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.
In AI infrastructure, PoC success does not always guarantee production success. Our Sales Engineering team exists to ensure that what we commit to with customers is scalable, efficient, economically viable, and aligned with platform strategy.
We are looking for a Lead Sales Engineer to lead and develop our Sales Engineering function while remaining deeply involved in our most strategic and technically complex customer engagements.
This is a player-coach role. You will lead a team of Sales Engineers, establish the technical standards and operating mechanisms for customer engagements, and personally provide architectural leadership on high-impact opportunities.
You will operate at the intersection of customer ambition, engineering reality, and commercial growth, ensuring the team consistently influences:
Revenue quality
Engineering focus and capacity
Product evolution
PoC-to-production conversion
Customer trust at scale
You’re welcome to work remotely from the United States.
Your responsibilities will include:
Team Leadership & Development
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 the growth of individual team members
Establish consistent approaches to discovery, architecture reviews, PoC 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
Strategic Technical Leadership
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 directly into critical opportunities when additional technical depth or leadership is required
Commercial Acceleration & Deal Governance
Partner closely with Sales leadership on strategic deals, account planning, and technical qualification
Influence deal strategy through architectural clarity and a strong understanding of customer requirements
Establish clear technical qualification and escalation mechanisms for complex opportunities
Ensure customer commitments are aligned with current or strategically planned platform capabilities
Prevent misaligned commitments before Engineering resources are allocated
Improve PoC-to-production conversion by ensuring technical and economic realism from the beginning
Help Sales and Sales Engineering balance customer urgency with sustainable platform development
PoC Architecture & Validation
Establish standards for how the team scopes, designs, and evaluates customer PoCs
Ensure measurable success criteria are defined, including latency, TTFT, throughput, reliability, and cost envelope
Guide workload classification and determine the appropriate depth of optimization
Align the right 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 R&D, and poorly scoped engineering commitments
Ensure successful PoCs have a clear and realistic path to production
Pattern Recognition & Platform Leverage
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
Help 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 wider Sales Engineering organization
Cross-Functional Leadership
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 that allow Product and Engineering to understand emerging customer demand
Help leadership make informed tradeoffs between revenue opportunity, customer impact, and engineering investment
We expect you to have:
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 – you understand 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
What success looks like:
The Sales Engineering team operates with clear standards, ownership, and technical rigor
Sales Engineering capacity is allocated predictably toward the highest-value opportunities
Strategic deals are technically sound before significant Engineering engagement
PoCs are consistently scoped, measurable, and economically justified
Technical risks and misaligned customer expectations are identified early
PoC-to-production conversion improves
Engineering teams spend less time on poorly qualified or one-off customer requirements
Repeatable customer patterns systematically influence Product and Engineering priorities
Sales has a trusted technical partner for navigating complex AI infrastructure opportunities
Customers view the Sales Engineering organization as trusted architectural advisors
Sales Engineers grow in technical depth, commercial judgment, and customer leadership
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
Base Compensation Range$228,000—$285,000 USDBenefits & Perks:
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
What's it like to work at Nebius:
Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI
Equal Opportunity Statement:
Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.
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.
If you need accommodations during the application process, please let us know.
Source: Nebius careers