At a Glance
- Tasks: Design and manage cutting-edge AI infrastructure for top global enterprises.
- Company: Fast-growing Series A deep tech company revolutionising AI infrastructure.
- Benefits: Competitive salary, dynamic work environment, and opportunities for professional growth.
- Other info: Collaborate with world-class engineers in a high-performance culture.
- Why this job: Join a team at the forefront of AI innovation and make a real impact.
- Qualifications: Experience in cloud infrastructure, Kubernetes, and strong problem-solving skills.
The predicted salary is between 36000 - 60000 £ per year.
Infrastructure AI Engineer – Series A Deep Tech AI Company
About the Company: Our client is a pioneering deep tech company transforming how enterprises leverage artificial intelligence to automate complex analytics workflows. Following a successful Series A funding round, the company is scaling rapidly to meet growing demand from some of the world's largest organizations. Their platform delivers AI‐powered digital workers — autonomous systems that perform sophisticated analytics and data science tasks continuously and intelligently.
The Role: As an Infrastructure AI Engineer, you'll design, deploy, and manage the infrastructure that powers some of the most advanced AI systems in production today. You'll work at the intersection of cloud computing, AI operations, and DevOps, ensuring scalable, secure, and high‐performing environments for enterprise AI deployments. This is a hands‐on, client‐facing role where you'll collaborate with technical and business teams to bring cutting‐edge AI agents and workflows to life across multi‐cloud and on‐premise environments.
What You'll Do:
- Architect, deploy, and maintain production‐grade AI solutions across multi‐cloud and on‐prem infrastructures.
- Design and manage Kubernetes‐based environments to support high‐performance AI workloads.
- Implement best practices for availability, observability, scalability, and security in AI infrastructure.
- Collaborate with enterprise clients to understand deployment constraints and design tailored solutions.
- Integrate and operationalize LLMs, RAGs, MCPs, and agentic AI workflows into robust environments.
- Build and optimize CI/CD pipelines and infrastructure‐as‐code (IaC) frameworks (e.g., Terraform, Helm).
- Partner closely with AI engineering teams to ensure smooth delivery from prototype to production.
What You'll Bring:
- Strong background in cloud infrastructure engineering — experience with at least one major provider (AWS, Azure, or GCP).
- Proven ability to deploy and manage systems across hybrid or multi‐cloud and on‐premise environments.
- Expertise with Kubernetes, Docker, and container orchestration at scale.
- Familiarity with DevOps and site reliability engineering (SRE) best practices.
- Experience with CI/CD automation and infrastructure‐as‐code tools.
- Understanding of AI/ML deployment patterns and how to support model‐driven workloads in production.
- Strong client‐facing communication and problem‐solving skills, with a forward‐deployed engineering mindset.
Why Join:
- Join a fast‐growing Series A company at the forefront of AI infrastructure innovation.
- Work on cutting‐edge, real‐world AI deployments for top global enterprises.
- Collaborate with world‐class engineers and AI practitioners in a high‐performance culture.
- Be part of a team that values ownership, excellence, and impact — where winning together is the goal.
Infrastructure Engineer (AI) in London employer: Space Executive
Join a pioneering deep tech startup in the UK that is revolutionising industries by eliminating outdated systems and enabling real-world work to move at software speed. With a world-class team and a culture of high trust and ownership, you'll have the opportunity to make a significant impact from day one, backed by substantial funding and a clear path for growth. This is not just a job; it's a chance to be part of something transformative in a high-intensity environment where your contributions truly matter.
StudySmarter Expert Advice🤫
We think this is how you could land Infrastructure Engineer (AI) in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to cloud infrastructure and AI. This gives you a chance to demonstrate your expertise beyond just a CV.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and scenarios related to Kubernetes, CI/CD, and AI deployments. Practise explaining your thought process clearly, as communication is key in client-facing roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Infrastructure Engineer (AI) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the Infrastructure AI Engineer role. Highlight your cloud infrastructure experience and any relevant projects you've worked on, especially those involving Kubernetes or multi-cloud environments.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI and how your background makes you a great fit for our team. Be specific about your achievements and how they relate to the responsibilities outlined in the job description.
Showcase Your Technical Skills:Don’t shy away from listing your technical proficiencies! Mention your experience with CI/CD tools, infrastructure-as-code, and any AI/ML deployment patterns you've worked with. This is your chance to shine!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows us you’re keen to join our team!
How to prepare for a job interview at Space Executive
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Kubernetes, Docker, and cloud providers. Brush up on your knowledge of AI/ML deployment patterns and be ready to discuss how you've applied these in real-world scenarios.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in previous roles. Think about times when you had to design tailored solutions for clients or optimise CI/CD pipelines. This will demonstrate your hands-on experience and client-facing communication skills.
✨Understand the Company’s Vision
Research the company’s mission and recent developments in AI infrastructure. Being able to articulate how your skills align with their goals will show that you’re genuinely interested and invested in their success.
✨Ask Insightful Questions
Prepare thoughtful questions that reflect your understanding of the role and the company. Inquire about their current projects, challenges they face in AI deployments, or how they measure success in their infrastructure. This shows your enthusiasm and strategic thinking.
