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Nscale

Develops and operates AI data centers

Staff Cloud Native Software Engineer

Full-TimeUpdated on 10/23/2026
$220k - $265k+ Bonus + Equity + Commission
Senior, Expert
Seattle, WA, USA+2 moreMore locations: Houston, TX, USA | San Francisco, CA, USA
In Person
Software EngineeringBackend Engineering

About the job

Requirements
  • At least 8 years of experience in production-level software development.
  • Deep hands-on experience building and operating Kubernetes-native software, such as custom controllers, operators, custom resources, or admission webhooks, using controller-runtime, client-go, or an equivalent.
  • Strong understanding of Kubernetes internals, including the API server, informer/lister patterns, reconciliation loops, and the object model.
  • Strong networking fundamentals, including Container Network Interface (CNI), service mesh, kube-proxy/eBPF datapaths, DNS, and load balancing, and experience building software that integrates with these systems.
  • Proficiency in Go or a similar language, with a track record of shipping well-tested, production-quality code at scale.
  • Experience with observability practices, including metrics, tracing, and structured logging, built into software rather than added afterward.
  • Ability to own components independently end-to-end, from design through operation, while setting direction for adjacent teams.
  • Track record of leading technical design at a staff level and mentoring engineers through practical technical guidance.
Responsibilities
  • Design, build, and operate Kubernetes-native software, including controllers, operators, custom resources, and admission webhooks, that connects AI applications with core networking components on GPU-backed infrastructure.
  • Extend Kubernetes control-plane capabilities to support AI workload requirements, including network policy controllers, CNI/service-mesh integrations, and resource/scheduling extensions.
  • Own significant components end-to-end and set technical direction for how they are designed, deployed, and operated across the team.
  • Build reconciliation loops, informers, and client-go-based tooling that keep infrastructure state consistent between the API server, networking systems, and AI runtime components.
  • Develop operational tooling and automation that make Kubernetes-native services easier for internal teams to deploy, run, and support.
  • Drive infrastructure architecture decisions about integrating AI applications and networking components across the platform, weighing trade-offs at a cross-team level.
  • Build observability foundations for controller and operator software, including metrics, structured events, tracing, and status reporting surfaced through the Kubernetes API and platform dashboards.
  • Design systems that degrade gracefully and self-heal, using controller patterns such as reconciliation, backoff, and status conditions to reduce manual intervention.
  • Debug and resolve complex issues spanning the Kubernetes control plane, networking, including CNI, service mesh, kube-proxy/eBPF datapaths, and workload runtime behavior on GPU-backed infrastructure.
  • Define standards for safe rollout of controller and platform changes, including versioning, compatibility, and staged deployment.
  • Set technical direction for how the team builds Kubernetes-native software, establishing patterns for controller design, custom resource schema evolution, and testing strategy.
  • Lead design discussions and code reviews, maintaining a high bar for Kubernetes API conventions and idiomatic client-go usage.
  • Partner with platform engineering, infrastructure, and product teams to translate developer and operational needs into clean custom resources, APIs, and controller-managed abstractions.
  • Define reusable patterns, shared libraries, and scaffolding that enable other teams to build correctly on the platform without reinventing integration logic.
  • Mentor engineers in Kubernetes internals, controller-runtime patterns, and sound operational judgment.
Desired Qualifications
  • Strong interest in or experience with GPU-backed infrastructure and AI workload patterns.
  • Go proficiency is strongly preferred.

About the company

Nscale operates as a vertically integrated AI infrastructure platform in London, owning data centers, GPU compute, networking, storage and managed AI cloud services for enterprises, governments and AI builders. It runs the full stack from sovereign European, renewables-powered campuses (including Norway hydropower) to US campus expansions, providing hosted AI capabilities and high-performance GPU resources. Its advantage comes from a tightly integrated stack and a focus on sovereign, renewable-powered deployments in Europe, supported by strong capital, partnerships (including NVIDIA) and strategic board members. The goal is to scale into a leading, globally capable AI infrastructure provider that lets governments and organizations deploy, run and manage AI workloads quickly and securely on sovereign, renewable-powered campuses.

Company Size

1,001-5,000

Company Stage

Debt Financing

Total Funding

$9.8B

Headquarters

London, United Kingdom

Founded

2024

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Simplify Jobs

Simplify's Take

What believers are saying

  • Nscale closed $3.36 billion convertible financing on September 25, 2026.
  • It filed for a NYSE IPO on September 18, 2026 under ticker NSCL.
  • Justin Osofsky joined October 2, 2026, strengthening global operations before listing.

What critics are saying

  • Nscale's largest customer drove 52% of first-half 2026 revenue.
  • First-half 2026 losses reached $1.02 billion against $140.6 million revenue.
  • A failed IPO or refinancing halts its gigawatt buildout and crushes solvency.

What makes Nscale unique

  • Nscale controls power, data centers, GPUs, networking, storage, and managed AI cloud.
  • It targets sovereign European deployments with renewable sites like Norway hydropower.
  • It already booked $103 billion TCV with Microsoft and Anthropic through 2033.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Unlimited Paid Time Off
  • Parental Leave
  • 401(k) Retirement Plan

Growth & Insights and Company News

6 month growth

19%

1 year growth

3%

2 year growth

-1%
Yahoo Finance
Oct 24th, 2026
Neocloud "death spiral" fears hit AI boom as CoreWeave's $32B debt and equity pile meets 16% rates

Shares in "neocloud" firms such as CoreWeave, Nebius and Iren have slumped as investors balk at heavy losses and high borrowing costs. Nvidia and Oracle shares are down 10% from their peak earlier this month. CoreWeave has raised $32bn in debt and equity to fund 51 data centres, yet reported revenue of just $4.6bn in the first six months of the year. Interest rates on some of its debt briefly hit 16% last week. HSBC analysts said its return on investment is 8.9%, well below borrowing costs, and judged it overvalued by 50%. Australia's Firmus has cancelled a £20bn IPO. Gartner analyst Will Sommer predicts 80% of neoclouds will cease independent operations by 2030, and that $3.5tn in AI infrastructure spending could be written off. Nvidia's chief executive, Jensen Huang, says the sector faces a "scarcity of capital", not weak demand.

Yahoo Finance
Oct 22nd, 2026
Nvidia's Huang told Nscale to "work around the clock" as $30B IPO target draws pushback

Nvidia chief executive officer Jensen Huang said he told UK-based neocloud Nscale to "work around the clock" to fix problems bringing some of its data centres online. Nscale, which Nvidia backs, has faced delays, equipment failures and power constraints, along with investor pushback over its $30 billion IPO valuation target. Speaking at Nvidia's GTC conference in Berlin, Huang said neoclouds will overcome their troubles because AI computing demand is high. "They just need working capital," he said. Other neoclouds have stumbled recently. Australia's Firmus Grid abandoned a $30 billion IPO, and South Korea's Elice had a difficult trading debut. Nvidia also unveiled the DSX Pod, a container-sized mini data centre that arrives with hardware, cabling and plumbing installed and tested.

City A.M.
Oct 22nd, 2026
Microsoft boss warns of AI trust crisis as UK workers lag behind bosses.

Microsoft boss warns of AI trust crisis as UK workers lag behind bosses. Tech Reporter Microsoft chief executive Satya Nadella has warned that increasingly powerful AI systems are becoming less trustworthy, as new research exposes a widening confidence gap between UK bosses and their employees. Speaking at Microsoft's Frontier Tour in London on Wednesday, Nadella urged businesses to embrace AI while retaining human oversight, warning that the technology's growing capabilities bring new risks. "Our scaling laws are producing even more powerful models that are less and less trustworthy", he said, arguing that businesses must treat AI systems as "new forms of insiders" and build safeguards around them. His warning comes as Microsoft research revealed that 84 per cent of UK business leaders believe Britain can become a world-leading AI economy within five years, compared with just 41 per cent of employees. The findings suggest a disconnect between executives pushing ahead with AI adoption and workers concerned about what the technology means for their jobs. Stay in the know Three daily briefings with the key market moves and top business and political stories. Employees cited fears over job security and fewer opportunities for younger workers among their concerns. Nadella said businesses must ensure AI strengthens rather than undermines employees' ability to work. "How do you put the human in the loop?" he asked. "How do you really ensure that, ultimately, that sense of empowerment is not lost?" He also warned that businesses risk losing control of valuable knowledge generated through AI systems, urging organisations to retain ownership of both their employees' expertise and the information produced by AI. Britain's AI ambitions face a reality check. The warnings come as the government seeks to position Britain as a global AI powerhouse, with billions pledged towards computing infrastructure and greater adoption across public services. But questions still remain over whether that investment will translate into higher productivity, particularly as businesses grapple with the cost of deploying AI systems and managing their risks. Microsoft itself has committed billions to UK infrastructure, although the country's AI expansion is increasingly constrained by electricity shortages and lengthy grid connection delays. Earlier this week, Microsoft withdrew from a planned £2bn AI data centre project in Essex after developer Nscale faced delays securing sufficient power until the 2030s. The setback highlighted the difficulties facing even the world's largest technology companies as they race to expand Britain's computing capacity. Meanwhile, Nadella highlighted Yorkshire Ambulance Service's use of Copilot to reduce administrative work in the NHS, ahead of plans to make the technology available to as many as 500,000 clinicians and support staff. But expanding access to AI tools is not the same as demonstrating sustained improvements in productivity or patient care. Microsoft's UK and Ireland chief executive Darren Hardman said businesses needed to establish clear limits on what AI systems could access and do. "You can set clear boundaries on the data AI can access. And the actions it can take. With human approval where it matters" he said.

CNC Seeker
Oct 22nd, 2026
Schneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twin.

Schneider Electric, AVEVA, Nscale and Start Campus pilot AI digital twin. Key takeaways. * Schneider Electric, AVEVA, Nscale and Start Campus have launched one of the first end-to-end AI-driven digital twins built on NVIDIA Omniverse DSX Blueprint. * The pilot runs in the 1.2 GW SIN01 data-center at Portugal's SINES Data Campus, soon to host >66,000 NVIDIA Rubin GPUs. * By merging real-time power, cooling and workload data, the Immersive Twin delivers a single, predictive view that can cut energy use by up to 15 % and speed up token-production cycles by 30 %. * The project validates a reusable blueprint for gigawatt-scale AI factories, paving the way for faster design-build-operate-maintain loops across Europe. Schneider Electric, AVEVA, Nscale & Start Campus unveil ai-powered digital twin pilot. Background. A consortium of four industry leaders - Schneider Electric (global energy-tech provider), AVEVA (industrial-software specialist), Nscale (full-stack AI cloud platform) and Start Campus (data-center developer/operator) - has announced a live demonstration of an AI-centric digital twin. The solution is constructed on the NVIDIA Omniverse DSX Blueprint, part of NVIDIA's DSX Sim suite for high-fidelity simulation and AI-ready infrastructure. What the Immersive Twin does. | Feature | Traditional Approach | Immersive Twin (DSX Blueprint) | | Data Integration | Separate SCADA, BMS, and workload logs; manual correlation | Unified model ingesting power, cooling, network and AI-workload telemetry in real time | | Simulation Fidelity | 2-D schematics, limited physics | Full 3-D physics-based simulation with GPU-accelerated thermal and electrical analysis | | Decision Latency | Hours-to-days for scenario testing | Sub-second "what-if" queries powered by NVIDIA RTX-A6000 GPUs | | Scalability | Up to a few MW per model | Designed for gigawatt-scale AI factories (1.2 GW campus) | | AI Integration | Post-processing analytics | Embedded generative AI for predictive maintenance and load-balancing | The Immersive Twin fuses Schneider Electric's EcoStruxure(TM) digital-twin framework with AVEVA's engineering suite (including the Unified Engineering and System Platform). Nscale supplies the AI workload orchestration, while Start Campus provides the physical plant - the SIN01 data-center on the 1.2 GW SINES Data Campus. Pilot scope. * Location: SIN01, part of the 1.2 GW SINES Data Campus, Portugal. * Hardware Footprint: Planned deployment of >66,000 NVIDIA Rubin GPUs (each delivering up to 130 TFLOPS FP16 performance). * Energy Target: Reduce overall PUE (Power Usage Effectiveness) from the current 1.35 to <=1.20 within 12 months. * Token Production: Accelerate Nscale's AI-token generation pipeline by 30 %, cutting average token-creation time from 45 min to ~31 min. The twin continuously ingests sensor streams (temperature, humidity, voltage, current) and AI workload metrics (GPU utilisation, memory bandwidth). It then runs GPU-accelerated thermal-fluid simulations to predict hot-spot formation and recommends real-time cooling set-point adjustments. Why it matters. * Energy Efficiency at Scale - With AI workloads projected to consume 30 % of global electricity by 2030, a 15 % reduction in data-center energy use translates to ≈150 MW saved across a typical gigawatt-scale campus. * Speed to Market - The ability to test hardware-software configurations virtually eliminates weeks of physical prototyping, enabling faster rollout of new AI services. * Reusability - The DSX Blueprint is packaged as a validated, exportable model, allowing other operators to replicate the workflow with minimal custom development. Future outlook. The consortium plans to extend the pilot to two additional sites in 2027, each targeting a minimum of 50 % higher GPU density. A roadmap includes integration with NVIDIA's DGX Cloud for seamless workload migration and the addition of generative AI assistants that can auto-generate optimisation scripts based on twin insights. Bottom line. The Schneider Electric-AVEVA-Nscale-Start Campus partnership demonstrates that a high-fidelity, AI-ready digital twin built on NVIDIA's Omniverse DSX Blueprint can deliver measurable energy savings, faster AI-token production, and a repeatable blueprint for gigawatt-scale AI factories. As AI workloads continue to dominate power consumption, such immersive twins will become essential tools for operators seeking to balance performance, sustainability and cost.

404 Media
Oct 21st, 2026
Historic chestnut grove caught in fight over Nscale's 2,250-acre West Virginia data center

A grove of American chestnut trees in Mason County, West Virginia, has become the centre of a fight over Nscale's planned 2,250-acre Monarch Compute Campus. The UK-based startup says its clients include Anthropic, Nvidia, and Microsoft. The trees stand on the former Clements State Tree Nursery, which Nscale does not yet own but has agreed to buy. Nscale says it never planned to bulldoze them. On October 10, Governor Patrick Morrisey announced the trees would be relocated in late 2027. A forest pathologist with the West Virginia American Chestnut Foundation says moved trees would die within two to five years. All the remaining trees carry the blight fungus. Residents also oppose the campus after September storm runoff flooded nearby properties. The state environmental regulator held a public comment session on October 20.