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- Tasks: Lead partner validation efforts and manage technical relationships with GPU infrastructure providers.
- Company: Fluidstack is an innovative AI Cloud Platform building GPU supercomputers for top-tier clients.
- Benefits: Enjoy competitive pay, health insurance, generous PTO, and remote work flexibility.
- Why this job: Join a motivated team focused on cutting-edge AI technology and impactful customer experiences.
- Qualifications: Experience with GPU-cloud infrastructure and strong customer-facing skills are essential.
- Other info: This role offers the chance to shape the future of AI infrastructure.
The predicted salary is between 43200 - 72000 £ per year.
About Fluidstack
Fluidstack is the AI Cloud Platform. We build GPU supercomputers for top AI labs, governments, and enterprises. Our customers include Mistral, Poolside, Black Forest Labs, Meta, and more.
Our team is small, highly motivated, and focused on providing a world class supercomputing experience. We put our customers first in everything we do, working hard to not just win the sale, but to win repeated business and customer referrals.
We hold ourselves and each other to high standards. We expect you to care deeply about the work you do, the products you build, and the experience our customers have in every interaction with us.
You must work hard, take ownership from inception to delivery, and approach every problem with an open mind and a positive attitude. We value effectiveness, competence, and a growth mindset.
Overview :
As we rapidly expand with new and existing partners to meet the demands of a growing customer base, we\’re seeking our founding Partner Solutions Architect to lead and scale our partner ecosystem. This is a highly technical and cross-functional role reporting directly to the Director of Partnerships.
You will be responsible for validating partner infrastructure, ensuring system health, and managing deep technical relationships with GPU infrastructure providers. Your work will directly influence the scalability, reliability, and performance of our platform.
Focus:
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Lead and scale partner validation efforts: Manage multiple concurrent infrastructure validation cycles, define and track KPIs, and build repeatable processes.
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Monitor and troubleshoot distributed systems: Perform end-to-end diagnostics across compute, fabric (e.g., InfiniBand), and storage layers.
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Stay current with cutting-edge trends in AI infrastructure such as NVIDIA Hopper/Blackwell architectures, model-serving patterns, and emerging ML system designs and disseminate insights internally and externally.
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Own technical partner relationships: Act as the primary technical contact for GPU capacity partners, balancing deep engineering discussions with high-level business context.
Qualifications:
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Technical depth in GPU-cloud infrastructure: Experience with large-scale GPU clusters using Kubernetes and/or SLURM over InfiniBand; deep understanding of the NVIDIA driver stack, NCCL performance tuning, and benchmarking.
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Strong customer or partner-facing experience: Able to bridge technical and business conversations, explain complex systems to mixed audiences, and build trust through technical credibility.
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Automation-first mindset: Skilled in infrastructure-as-code (Terraform or Pulumi), CI/CD workflows, observability stacks (Prometheus, Grafana, Loki), and scripting (Python, Bash).
Bonus: Prior experience working with GPU capacity providers, hyperscaler partnerships, or AI infrastructure startups.
Benefits:
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Competitive total compensation package.
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Retirement or pension plan, in line with local norms.
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Health, dental, and vision insurance.
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Generous PTO policy, in line with local norms.
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Fluidstack is remote first, but has offices in key hubs. For all other locations, we provide access to WeWork.
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Partner Solutions Architect employer: FluidStack
Contact Detail:
FluidStack Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Partner Solutions Architect
✨Tip Number 1
Familiarise yourself with the latest trends in AI infrastructure, especially around GPU technologies like NVIDIA Hopper and Blackwell architectures. This knowledge will not only help you in interviews but also demonstrate your commitment to staying current in a rapidly evolving field.
✨Tip Number 2
Network with professionals in the AI and GPU infrastructure space. Attend relevant meetups, webinars, or conferences to connect with potential colleagues and industry leaders. Building these relationships can provide valuable insights and may even lead to referrals.
✨Tip Number 3
Prepare to discuss your experience with large-scale GPU clusters and automation tools like Terraform or Pulumi. Be ready to share specific examples of how you've managed infrastructure validation cycles or improved system performance in previous roles.
✨Tip Number 4
Showcase your ability to bridge technical and business conversations. Practice explaining complex systems in simple terms, as this skill is crucial for building trust with partners and customers alike. Highlight any past experiences where you've successfully navigated these discussions.
We think you need these skills to ace Partner Solutions Architect
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications of the Partner Solutions Architect position. Tailor your application to highlight relevant experiences that align with the job description.
Highlight Technical Skills: Emphasise your technical expertise in GPU-cloud infrastructure, Kubernetes, and automation tools like Terraform or Pulumi. Provide specific examples of projects where you've successfully applied these skills.
Showcase Customer Interaction Experience: Since the role requires strong customer-facing skills, include examples of how you've effectively communicated complex technical concepts to non-technical audiences. This will demonstrate your ability to bridge the gap between technical and business discussions.
Craft a Compelling Cover Letter: Write a cover letter that not only summarises your qualifications but also expresses your passion for AI infrastructure and your desire to contribute to Fluidstack's mission. Make it personal and engaging to stand out from other applicants.
How to prepare for a job interview at FluidStack
✨Show Your Technical Expertise
Make sure to highlight your experience with GPU-cloud infrastructure, especially with large-scale GPU clusters and Kubernetes. Be prepared to discuss specific projects where you've applied your technical skills, particularly in performance tuning and benchmarking.
✨Demonstrate Your Problem-Solving Skills
Fluidstack values an open mind and a positive attitude towards problem-solving. Prepare examples of how you've approached complex technical challenges in the past, particularly in distributed systems, and how you successfully resolved them.
✨Bridge Technical and Business Conversations
Since this role involves managing partner relationships, practice explaining complex technical concepts in simple terms. Think of ways to demonstrate your ability to build trust and credibility with both technical and non-technical stakeholders.
✨Stay Updated on Industry Trends
Fluidstack is looking for someone who is current with cutting-edge trends in AI infrastructure. Research recent developments in NVIDIA architectures and model-serving patterns, and be ready to share your insights during the interview.
