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- Tasks: Lead technical engagements and design scalable AI infrastructure solutions.
- Company: Dynamic tech firm focused on AI infrastructure with a collaborative culture.
- Benefits: Competitive salary, annual bonus, flexible working, and career development opportunities.
- Other info: Exciting projects with immediate impact and excellent growth potential.
- Why this job: Join a cutting-edge team and shape the future of AI technology.
- Qualifications: Experience in customer-facing technical roles and strong knowledge of AI infrastructure.
The predicted salary is between 90000 - 110000 £ per year.
We're looking for 3 Solutions Architects to lead technical engagements across its growing AI infrastructure practice. This is an integral pre-sales role that sits between technical depth and commercial delivery, translating complex customer challenges into scalable, production-ready AI infrastructure solutions.
You will work on large-scale GPU deployments, distributed training and inference architectures, high-performance networking fabrics, and the software stack that makes it all run. The business has the relationships, credentials, and pipeline to give this hire immediate traction.
You’ll partner closely with account teams throughout the full sales cycle. This role requires equal parts technical depth and commercial acumen. You will need to be as comfortable presenting ROI trade-offs and risk summaries to a CTO as you are discussing GPU memory bandwidth constraints or RDMA topology with an infrastructure engineering team.
- Run structured discovery to understand AI workload goals (training vs. qualification).
- Qualify opportunities early and advise account teams on architecture direction, risk, and deal strategy.
- Design end-to-end AI infrastructure architectures spanning GPU-accelerated compute, networking (Ethernet/InfiniBand/RoCE), storage, and the full software stack.
- Author and review technical proposal content: architecture diagrams, BOM guidance, SoW inputs, risk/mitigation summaries, and acceptance criteria.
- Help account teams articulate differentiation on performance, TCO, time-to-value, and supportability in competitive situations.
- Ensure clean transitions from pre-sales to implementation with validated designs, clear requirements, and agreed acceptance criteria.
Proven experience in a customer-facing technical role supporting complex infrastructure or platform deals is essential. Strong technical literacy across enterprise and AI infrastructure is required, including:
- GPU servers, PCIe/NVLink-class interconnects, networking fabrics (Ethernet, InfiniBand, RoCE), storage fundamentals, and Linux-based operations.
- Ability to translate workload and business goals into practical architectures with clear assumptions, trade-offs, and sizing across performance, cost, power, reliability, and security.
- Consultative engagement skills: able to lead technical conversations, handle objections, and partner with account teams to progress and close deals.
- Genuine curiosity about AI infrastructure: stays current on accelerator platforms, model trends, and the relationship between infrastructure choices and training/inference performance.
- Hands-on experience with AI/HPC orchestration platforms (Kubernetes, Slurm, Ray) and familiarity with GPU software stacks, CUDA ecosystem, container runtimes, driver management, libraries.
- Knowledge of networking for distributed AI workloads.
- Experience producing pre-sales assets: reference architectures, sizing guides, benchmark reports, TCO/ROI models, and competitive battlecards.
- Exposure to enterprise buying requirements: security/compliance, on-premises deployment constraints, procurement processes, and hardware lifecycle/lead-time realities.
Relevant vendor or industry certifications are a bonus.
Digital Solution Architect, flexible working employer: asobbi
Contact Detail:
asobbi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Digital Solution Architect, flexible working
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI infrastructure space. Attend meetups, webinars, or industry events. You never know who might be looking for someone just like you!
✨Tip Number 2
Show off your skills! Create a portfolio that highlights your experience with GPU deployments and AI architectures. Use real-world examples to demonstrate how you've tackled complex challenges. This will make you stand out when chatting with potential employers.
✨Tip Number 3
Practice your pitch! Be ready to discuss both technical details and business impacts. Whether you're talking to a CTO or an engineering team, being able to switch gears smoothly will show you're the complete package.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities waiting for you. Plus, it’s a great way to get noticed by our hiring team. Don’t miss out on your chance to join us in shaping the future of AI infrastructure!
We think you need these skills to ace Digital Solution Architect, flexible working
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Digital Solution Architect. Highlight your experience with AI infrastructure, GPU deployments, and any relevant technical skills that match the job description. We want to see how you can bring value to our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI infrastructure and how your background makes you the perfect fit for this role. Don’t forget to mention your consultative engagement skills and any hands-on experience you have.
Showcase Your Technical Depth: In your application, be sure to demonstrate your technical literacy across enterprise and AI infrastructure. Discuss your familiarity with GPU servers, networking fabrics, and orchestration platforms like Kubernetes. We love seeing candidates who can bridge the gap between tech and commercial delivery!
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any important updates. Plus, it shows you’re keen on joining the StudySmarter family!
How to prepare for a job interview at asobbi
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical aspects of AI infrastructure. Brush up on GPU deployments, networking fabrics, and the software stack. Being able to discuss these topics confidently will show that you have the depth needed for the role.
✨Understand the Business Side
Don’t just focus on the tech; understand how it translates into business value. Be prepared to discuss ROI trade-offs and risk summaries. This will demonstrate your ability to bridge the gap between technical depth and commercial delivery.
✨Prepare for Structured Discovery
Think about how you would run a structured discovery session to understand AI workload goals. Prepare questions that can help you uncover customer challenges and articulate how your solutions can address them effectively.
✨Showcase Your Consultative Skills
Be ready to lead technical conversations and handle objections. Practice articulating complex ideas simply and clearly. This will highlight your consultative engagement skills and your ability to partner with account teams to close deals.