AI Infrastructure Engineer

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We are a startup building foundational technology to address performance, scalability, and resiliency challenges in large-scale AI data center clusters. We are backed by top-tier VC firms and notable angel investors.
The company is led by experienced builders and operators who have founded companies, taken them to scale, and exited successfully. We work with a strong sense of unity and shared responsibility, and we expect trust, integrity, and respect in how we collaborate and make decisions. We hold ourselves accountable to one another and to the quality of the work we deliver.
Headquartered in Silicon Valley, we operate across a mix of remote and on-site locations in the U.S., Canada, and the U.K. We aim to create an environment where people are treated fairly, supported in their growth, and are empowered to do meaningful work alongside others who take the craft seriously.
Some Recent Press:
https://www.reuters.com/business/delos-data-chip-startup-founded-by-intel-veterans-raises-100-million-ai-networks-2026-09-15/
We are looking for:
We are looking for a talented Forward Deployed Engineer to be embedded with one of our strategic customers running our software in production. In this role, you will work hands-on inside the customer's AI data center environment, solving hard deployment and operational problems and turning what you learn into new product features alongside our engineering team. While most of your time will go to this customer, you will also bring your field experience to future customer pursuits, contributing hands-on to RFPs, technical evaluations, and new deployments. We are looking for a "builder" who has built and run AI infrastructure at scale, ideally at a neocloud or frontier AI lab, and who thrives on solving real problems in production.
Key Responsibilities
Serve as the dedicated technical owner for a strategic customer's production deployment of our software.

Work hands-on in the customer's AI data center environment, including GPU/XPU clusters, high-speed fabrics, schedulers, and orchestration layers.

Lead integration, troubleshooting, performance tuning, and root-cause analysis for production issues.

Guide the customer through software upgrades, cluster expansion, and new feature rollouts.

Build runbooks, integration guides, and automation tailored to the customer's environment.

Build deep working relationships with the customer's infrastructure, SRE, and platform engineering teams.

Turn customer problems into clear technical requirements and work with our engineering team to design and deliver new features.

Write and test code (Python, Bash, APIs) to prototype fixes, integrations, and tooling in the field.

Feed structured insights on bugs, feature gaps, and competitive needs back into product and engineering, and align customer milestones with our product release cycles.

Contribute hands-on technical work to RFPs, RFIs, technical evaluations, and proof-of-concept deployments for new customers.

Help build reference architectures, demo environments, and technical collateral, and represent the company at customer briefings, technical workshops, and industry events as needed.

Required Skills and Qualifications
5+ years in a hands-on infrastructure engineering role (forward deployed engineer, SRE, platform engineer, solutions architect, or similar) with direct customer or internal-customer exposure.

Proven AI data center experience: deploying and operating GPU/XPU clusters with high-speed interconnects (InfiniBand/RoCE/Ethernet/NVLink), job scheduling, and training/inference workloads.

Strong software problem-solving skills, including debugging complex distributed systems and writing production-quality scripts and tools in Python and Bash.

Hands-on experience with AI infrastructure software such as Kubernetes, Slurm, Tinkerbell, Canonical MaaS, observability stacks, or infrastructure management platforms.

Deep proficiency with Linux, containers, and APIs.

Track record of working with engineering teams to define and ship features based on field needs.

Clear communicator, comfortable whiteboarding with SREs and briefing senior infrastructure leaders.

Willingness to work on-site with the customer and travel as needed.

Desired Skills
Experience as a forward deployed or embedded engineer dedicated to a single large customer.

Experience taking early-stage or pre-launch products into hyperscale, neocloud, or AI lab environments.

Familiarity with inference serving and performance optimization (e.g., KV-cache behavior, disaggregated serving, GPU utilization analysis).

Background with observability stacks (Prometheus, Grafana, OpenTelemetry) and data pipelines for infrastructure analytics.

Prior experience at an AI infrastructure software vendor, GPU cloud provider, networking vendor, or hyperscaler.

Education
Bachelor's or Master's degree in Computer Engineering, Computer Science, Electrical Engineering, or a related field, or equivalent practical experience.

Location
This role is on-site at customer’s office based in Cambridge, UK.
Compensation
Target base salary for this role is £115k–£135k per year + equity. Our salary ranges are determined by role, level, experience, and location.
We are an equal opportunity employer. We value a range of perspectives and experiences and make employment decisions based on merit and business needs. We do not discriminate on the basis of legally protected characteristics.
Agency Note:
We do not accept resumes from agencies or search firms. Please do not forward candidate profiles through our careers page, email, LinkedIn messages, or directly to company employees. Any resumes submitted will be deemed the property of the company, and no fees will be paid in the event the candidate is hired.
#LI-EW1

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我们是一家初创公司，正在构建基础技术，以解决大规模AI数据中心集群中的性能、可扩展性和弹性挑战。我们得到了顶级风险投资公司和知名天使投资人的支持。
公司由经验丰富的建设者和运营者领导，他们曾创立公司，将其扩展规模，并成功退出。我们以强烈的团结感和共同责任感工作，期望在协作和决策过程中体现信任、诚信和尊重。我们对彼此和对我们交付的工作质量负责。
总部位于硅谷，我们在美国、加拿大和英国运营混合的远程和现场办公地点。我们致力于创造一个公平对待员工、支持他们成长、并让他们与认真对待手工艺的人一起从事有意义的工作的环境。
近期媒体报道：
https://www.reuters.com/business/delos-data-chip-startup-founded-by-intel-veterans-raises-100-million-ai-networks-2026-09-15/

我们正在寻找：
我们正在寻找一位才华横溢的前置部署工程师，将与我们的战略客户一起工作，该客户正在生产环境中运行我们的软件。在此职位中，您将在客户的AI数据中心环境中亲自动手工作，解决部署和运营难题，并与我们的工程团队一起将所学转化为新产品功能。虽然您的大部分时间将投入给该客户，但您还将把现场经验带到未来的客户业务中，为提案请求(RFP)、技术评估和新部署提供实际贡献。我们正在寻找一位"建设者"，他们曾大规模构建和运行AI基础设施，最好是在新云(neocloud)或前沿AI实验室中，并且热衷于在生产环境中解决实际问题。

主要职责
担任战略客户生产部署中我们软件的专职技术负责人。
在客户的AI数据中心环境中亲自动手工作，包括GPU/XPU集群、高速网络、调度程序和编排层。
领导集成、故障排除、性能调优和根本原因分析，解决生产问题。
指导客户完成软件升级、集群扩展和新功能发布。
构建针对客户环境的运行手册、集成指南和自动化工具。
与客户的基础设施、SRE(网站可靠性工程)和平台工程团队建立深厚的工作关系。
将客户问题转化为明确的技术需求，与我们的工程团队合作设计和交付新功能。
编写和测试代码(Python、Bash、APIs)，在现场原型化修复方案、集成和工具。
将关于错误、功能差距和竞争需求的结构化见解反馈给产品和工程团队，并将客户里程碑与我们的产品发布周期对齐。
为新客户的提案请求(RFP)、信息请求(RFIs)、技术评估和概念验证部署提供实际技术工作。
帮助构建参考架构、演示环境和技术资料，并根据需要在客户简报、技术研讨会和行业活动中代表公司。

所需技能和资格
5年以上基础设施工程实际操作经验(前置部署工程师、SRE、平台工程师、解决方案架构师或类似职位)，具有直接客户或内部客户接触经验。
有AI数据中心经验：部署和操作具有高速互连(InfiniBand/RoCE/Ethernet/NVLink)的GPU/XPU集群，作业调度，以及训练/推理工作负载。
强大的软件问题解决能力，包括调试复杂分布式系统和编写生产质量的Python和Bash脚本及工具。
具有AI基础设施软件的实际操作经验，如Kubernetes、Slurm、Tinkerbell、Canonical MaaS、可观察性堆栈或基础设施管理平台。
对Linux、容器和API有深入了解。
与工程

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