Senior Sales Engineer（远程职位）

这条招聘信息来自 Nebius，岗位是 Senior Sales Engineer：这是高级职位，公司期待由你自己拿主意。职位属于「IT 与编程」类别，完全远程。公司不限制候选人的居住地，在任何地方都可以申请。

公司没有公布具体数字，这一项会在面试时谈定。对工作时间，招聘信息没有提出任何条件。

这个职位通过了自动核查：凡是要求外国工作许可、签证担保、特定国籍，或者必须居住在指定国家的招聘信息，都不会进入列表。

Why work at Nebius Nebius is leading a new era in cloud computing to serve the global AI economy. We create the tools and resources our customers need to solve real-world challenges and transform industries, without massive infrastructure costs or the need to build large in-house AI/ML teams. Our employees work at the cutting edge of AI cloud infrastructure alongside some of the most experienced and innovative leaders and engineers in the field.

Where we workHeadquartered in Amsterdam and listed on Nasdaq, Nebius has a global footprint with R&D hubs across Europe, North America, and Israel. The team of over 800 employees includes more than 400 highly skilled engineers with deep expertise across hardware and software engineering, as well as an in-house AI R&D team.

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 guarantee production success. This role ensures that what we commit to is scalable, efficient, and aligned with platform strategy. We 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. You will operate at the intersection of customer ambition, engineering reality, and commercial growth, influencing:

* Revenue quality

* Engineering focus

* Product evolution

* Customer trust at scale

You’re welcome to work remotelyfrom Europe. Your responsibilities will include: Strategic Technical Discovery

* Lead deep technical discovery with engineering teams and technical founders

* Understand model requirements, traffic expectations, latency constraints, GPU economics, and system dependencies

* Translate customer ambition into production-feasible architectures

* Identify hidden technical risks early

Commercial Acceleration

* Partner tightly with Sales on strategic deals

* Influence deal strategy through architectural clarity

* Prevent misaligned commitments before engineering allocation

* Increase PoC-to-production conversion by ensuring technical realism

PoC Architecture & Validation

* Define measurable success criteria (latency, TTFT, throughput, cost envelope)

* Classify workload complexity and required optimization depth

* Align appropriate resources (ML Solution Architects, engineering, GPU capacity, etc.)

* Drive structured Go / No-Go decisions

* Prevent uncontrolled customization or hidden R&D

Pattern Recognition & Platform Leverage

* Identify recurring configuration patterns across customers

* Quantify demand for advanced optimizations (quantization, speculative decoding, etc.)

* Surface structured insights to Product and Engineering

* Help evolve platform capabilities based on real workload data

We expect you to have:

* Deep understanding of AI inference systems and GPU-backed infrastructure

* Experience with LLM workloads and performance-sensitive environments

* Experience with inference frameworks and libraries (e.g., vLLM, SGLang, TensorRT-LLM).

* Ability to reason about latency, throughput, cost, and architecture tradeoffs

* Strong customer presence with engineering-first organizations

* Comfort challenging assumptions and pushing back constructively

* Commercial awareness - you understand that engineering time is a strategic resource

Preferred technical stack:

* Programming Languages- Python

* Frameworks and Libraries- vLLM, SGLang, TensorRT-LLM, OpenAI/Anthropic SDKs

* Frameworks for Agentic Pipelines : Langchain / Langsmith / smolagents / equivalent

* API and Web Frameworks- FastAPI, Flask

* MLOps and DevOps tools- Kubernetes (K8s), Docker, Git

* Cloud Platforms- AWS (SageMaker, Bedrock), GCP (Vertex AI), Azure (Azure ML)

What success looks like:

* Strategic deals are technically sound before engineering engagement

* PoCs are clearly scoped and economically justified

* Engineering capacity is allocated predictably

* Conversion to production improves

* Customers view you as a trusted architectural advisor

What we offer

* Competitive salary and comprehensive benefits package.

* Opportunities for professional growth within Nebius .

* Flexible working arrangements.

* A dynamic and collaborative work environment that values initiative and innovation.

We’re growing and expanding our products every day. If you’re up to the challenge and are excited about AI and ML as much as we are, join us!

Originally posted on Himalayas