{"id":2350316,"url":"https://alion.io/job/nebius-senior-sales-engineer-token-factory-2","title":"Senior Sales Engineer - Token Factory","company":{"id":6364,"name":"Nebius","domain":"nebius.com","url":"https://alion.io/company/nebius","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":84,"open_postings":106,"ghost_share":0,"stale_share":0.651,"repost_share":0,"time_to_fill_p50_days":57,"computed_at":"2026-10-30T05:48:23Z"}},"role":"Solutions","role_family":"Solutions","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["DE","FR","GB","AT","BE","BG","HR","CZ","DK","FI","HU","IE","IT","NL","NO","PL","RO","ES","SE","CH","EE","GR","IS","LV","LI","LT","LU","MT","PT","SK","SI"],"hiring_countries_total":31,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":312000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":1900},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Go","optional":false},{"name":"LLM","optional":false},{"name":"Quantization","optional":false},{"name":"SGLang","optional":false},{"name":"Speculative Decoding","optional":false},{"name":"TensorRT-LLM","optional":false},{"name":"vLLM","optional":false},{"name":"Amazon SageMaker","optional":true},{"name":"Anthropic","optional":true},{"name":"AWS","optional":true},{"name":"AWS Bedrock","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"FastAPI","optional":true},{"name":"Flask","optional":true},{"name":"GCP","optional":true},{"name":"Git","optional":true},{"name":"Kubernetes","optional":true},{"name":"LangChain","optional":true},{"name":"LangSmith","optional":true},{"name":"OpenAI","optional":true},{"name":"Python","optional":true},{"name":"smolagents","optional":true},{"name":"TensorRT","optional":true},{"name":"Vertex AI","optional":true}],"status":"live","first_seen_at":"2026-10-12T10:29:05Z","employer_posted_date":"2026-10-13","last_verified_at":"2026-10-30T08:02:43Z","board_verified":true,"closed_at":null,"days_open":17,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":17},"description":"About Nebius:\nNebius 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.\nBuilt by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.\nListed 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.\nThe role \nWe are building a high-performance AI inference platform for developer-native teams running latency- and cost-sensitive workloads at scale.\nIn AI infrastructure, PoC success does not guarantee production success. This role ensures that what we commit to is scalable, efficient, and aligned with platform strategy.\nWe are looking for a Senior Sales Engineer to become a foundational technical partner to our customers and a force multiplier for Sales and Engineering. You will shape complex AI workloads from first discovery through production feasibility validation, ensuring technical rigor, economic viability, and scalable architecture decisions.\nYou will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:\nRevenue quality\nEngineering focus\nProduct evolution\nCustomer trust at scale\nYou’re welcome to work remotely from Europe.\nYour responsibilities will include: \nStrategic Technical Discovery\nLead deep technical discovery with engineering teams and technical founders\nUnderstand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies\nTranslate customer ambition into production-feasible architectures\nIdentify hidden technical risks early\nCommercial Acceleration\nPartner tightly with Sales on strategic deals\nInfluence deal strategy through architectural clarity\nPrevent misaligned commitments before engineering allocation\nIncrease PoC-to-production conversion by ensuring technical realism\nPoC Architecture & Validation\nDefine measurable success criteria (latency, TTFT, throughput, cost envelope)\nClassify workload complexity and required optimization depth\nAlign appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)\nDrive structured Go / No-Go decisions\nPrevent uncontrolled customization or hidden R&D\nPattern Recognition & Platform Leverage\nIdentify recurring configuration patterns across customers\nQuantify demand for advanced optimizations (quantization, speculative decoding, etc.)\nSurface structured insights to Product and Engineering\nHelp evolve platform capabilities based on real workload data\nWe expect you to have: \nDeep understanding of AI inference systems and GPU-backed infrastructure\nExperience with LLM workloads and performance-sensitive environments\nExperience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).\nAbility to reason about latency, throughput, cost, and architecture tradeoffs\nStrong customer presence with engineering-first organizations\nComfort challenging assumptions and pushing back constructively\nCommercial awareness - you understand that engineering time is a strategic resource\nPreferred technical stack: \nProgramming Languages- Python\nFrameworks and Libraries- vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs\nFrameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent\nAPI and Web Frameworks- FastAPI, Flask\nMLOps and DevOps tools- Kubernetes (K8s), Docker, Git\nCloud Platforms- AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)\nWhat success looks like: \nStrategic deals are technically sound before engineering engagement\nPoCs are clearly scoped and economically justified\nEngineering capacity is allocated predictably\nConversion to production improves\nCustomers view you as a trusted architectural advisor\nBenefits & Perks:\nCompetitive compensation\nCareer growth and learning opportunities\nFlexibility and ownership\nCollaborative and innovative culture\nOpportunity to work on impactful AI projects\nInternational environment and talented teams\nWhat's it like to work at Nebius:\nFast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI \nEqual Opportunity Statement:\nNebius 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.\nApplicants 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. \nIf you need accommodations during the application process, please let us know.","description_format":"text","description_chars":5267,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Germany","iso":"DE","kind":"region"},{"name":"France","iso":"FR","kind":"region"},{"name":"United 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