Nscale
Senior Cloud Native Platform Engineer

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About Nscale
Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.
We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you’ll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you’ll be contributing to building the technology that powers the future.
About The Role
Nscale is the GPU cloud engineered for AI. We provide cost-effective, high-performance infrastructure for AI start-ups and large enterprise customers. Nscale enables AI-focused companies to achieve superior results by reducing the complexity of AI development. Our GPU cloud bolsters technical capabilities and directly supports strategic business outcomes, including cost management, rapid innovation, and environmental responsibility.
We thrive on a culture of relentless innovation, ownership, and accountability, where every team member takes pride in their work and drives it with excellence and urgency. As an Nscaler, you’ll build trust through openness and transparency, where everyone is inspired to do their best work. If you join our team, you’ll be contributing to building the technology that powers the future.
What You'll Be Doing
Platform Operations & Engineering
- Build and improve shared cloud-native platform capabilities used by internal engineering teams to run AI applications and services.
- Own significant parts of the platform area, including Kubernetes cluster operations, workload runtime configuration, deployment workflows, observability foundations, or environment automation.
- Improve the reliability, scalability, and supportability of platform services through practical engineering and operational enhancements.
- Develop automation, tooling, and configuration that reduce manual effort, improve consistency, and make the platform easier to use and operate.
- Apply software engineering where it creates leverage, including scripts, services, CI/CD automation, operational tooling, and platform integrations.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Reliability, Operability & Automation
- Improve incident prevention, detection, response, and recovery across the platform areas you support.
- Build and refine observability for platform services, including metrics, logs, tracing, dashboards, alerts, and other useful operational signals.
- Strengthen rollout safety, capacity awareness, failure handling, and recovery procedures for production environments.
- Debug and resolve complex issues spanning Kubernetes, Linux, networking, storage, workload runtime behaviour, and cloud or datacentre infrastructure dependencies.
- Enhance operational playbooks, runbooks, and engineering practices to reduce toil and increase service resilience.
Team Technical Contribution
- Contribute to design discussions, code reviews, and operational standards within the platform engineering team.
- Collaborate with software engineering, infrastructure, and SRE teams to deliver platform capabilities that are practical, supportable, and aligned to operational needs.
- Define sensible defaults, paved roads, and supportable patterns for service deployment and runtime operations.
- Mentor less experienced engineers in platform engineering fundamentals, operational judgement, and good automation practices.
KPIs
- Platform reliability and service resilience
- Reduction in manual operational toil
- Incident detection, response, and recovery effectiveness
- Observability and operational readiness of platform services
About You
- Strong hands-on experience operating and improving Kubernetes-based platforms in production.
- Solid experience with infrastructure automation, CI/CD, configuration management, or GitOps-style workflows.
- Strong understanding of reliability engineering principles, including observability, incident response, failure analysis, and operational readiness.
- Experience writing production-quality automation, tooling, or backend code in Go, Python, Bash, or similar languages.
- Good Linux fundamentals, including processes, filesystems, cgroups, service behaviour, and system debugging.
- Good networking fundamentals, including TCP/IP, DNS, routing, load balancing, and container or overlay networking concepts.
- Experience debugging complex production issues across multiple system layers.
- Ability to work independently on substantial technical problems while collaborating effectively with adjacent teams.
- Experience mentoring or supporting less experienced engineers through practical technical guidance.


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What We Can Offer You
You’ll have the opportunity to help shape the operating standards behind a next-generation AI cloud platform, working on complex infrastructure challenges with real ownership and impact. This is a chance to play a meaningful role in scaling high-performance, sustainable data centre operations in a fast-moving environment.
Equal Opportunities Statement
We strongly encourage applications from people of colour, the LGBTQ+ community, people with disabilities, neurodivergent people, parents, carers, and people from lower socio-economic backgrounds.
If there’s anything we can do to accommodate your specific situation, please let us know.
The responsibilities outlined in this job description are not exhaustive and are intended to provide a general overview of the position. The employee may be required to perform additional duties, tasks, and responsibilities as assigned by management, consistent with the skills and qualifications required for the role.
For information on how Nscale handles candidate personal data, please see our Employee & Candidate Privacy Notice.
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