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- Tasks: Design and deliver high-performance GPU cloud environments for AI workloads.
- Company: Global tech company focused on innovative solutions.
- Benefits: Competitive salary, remote work flexibility, and opportunities for professional growth.
- Why this job: Join a cutting-edge team and tackle complex challenges in AI and GPU technology.
- Qualifications: Experience with GPU compute, HPC, and AI/ML workloads required.
- Other info: Remote role with occasional travel; excellent career advancement potential.
The predicted salary is between 120000 - 150000 £ per year.
A global technology company is looking for a Solution Architect to design and deliver high-performance GPU cloud environments. You’ll work directly with customers, engineering, and infrastructure teams to ensure AI workloads run efficiently at scale.
Who This Role Is For
Hands-on architects with deep experience in GPU, HPC, or AI/ML infrastructure. You’re comfortable bridging technical teams and customer needs, solving complex scaling challenges, and owning architectural decisions in a remote contract environment.
Key Responsibilities
- Design GPU solutions, including cluster sizing, networking, and performance optimization.
- Provide guidance on compute, storage, networking, and deployment architectures.
- Identify performance or scaling bottlenecks and recommend improvements.
- Support customer onboarding, proofs of concept, and production deployments.
What They’re Looking For
- Strong experience with GPU compute, HPC, and AI/ML workloads.
- Solid understanding of networking (L2/L3, InfiniBand, RoCE) and storage systems.
- Hands-on experience deploying or supporting GPU clusters.
- Experience with Kubernetes and Terraform in production environments.
Interview Process: 15 Min Call with Talent, 2x Technical Calls (60 min). Very occasional travel to customer sites will be required.
If you are interested in the role and would like to know more, please reach out with your latest CV and I will be in touch if relevant.
Solutions Architect (C#, .NET) in Stoke-on-Trent employer: TechShack
Contact Detail:
TechShack Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solutions Architect (C#, .NET) in Stoke-on-Trent
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work with GPU and AI/ML. Join relevant online communities or forums where you can share insights and learn from others. You never know who might have a lead on your dream job!
✨Tip Number 2
Prepare for those technical calls! Brush up on your knowledge of GPU compute, networking, and Kubernetes. Practise explaining complex concepts in simple terms, as you'll need to bridge the gap between tech teams and customer needs.
✨Tip Number 3
Showcase your hands-on experience! During interviews, be ready to discuss specific projects where you've deployed or supported GPU clusters. Highlight any challenges you faced and how you overcame them—this will demonstrate your problem-solving skills.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take that extra step to connect with us directly.
We think you need these skills to ace Solutions Architect (C#, .NET) in Stoke-on-Trent
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with GPU, HPC, and AI/ML workloads. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for this Solutions Architect role. We love seeing your personality come through, so feel free to share your passion for technology and problem-solving.
Showcase Your Technical Skills: In your application, make sure to mention your hands-on experience with Kubernetes, Terraform, and GPU clusters. We’re looking for someone who can hit the ground running, so let us know how you’ve tackled similar challenges in the past.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to keep track of your application and ensure it gets the attention it deserves. Plus, it makes the whole process smoother for everyone involved!
How to prepare for a job interview at TechShack
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of GPU compute, HPC, and AI/ML workloads. Be ready to discuss specific projects where you've designed or optimised GPU solutions, as well as any challenges you faced and how you overcame them.
✨Understand the Customer's Needs
Since this role involves working directly with customers, it’s crucial to demonstrate your ability to bridge technical teams and customer requirements. Prepare examples of how you've successfully supported customer onboarding or managed proofs of concept in the past.
✨Showcase Your Problem-Solving Skills
Be prepared to discuss how you've identified performance or scaling bottlenecks in previous roles. Think of specific instances where you recommended improvements and the impact those changes had on the project or team.
✨Familiarise Yourself with Tools
Since experience with Kubernetes and Terraform is essential, make sure you can talk about your hands-on experience with these tools. Consider preparing a brief overview of a project where you deployed or supported GPU clusters using these technologies.