At a Glance
- Tasks: Design and build secure cloud-native infrastructure for AI workloads at scale.
- Company: Join a top-tier Hedge Fund leading in AI innovation.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic role with a focus on security and scalability in a fast-paced environment.
- Why this job: Be at the forefront of AI technology and make a significant impact.
- Qualifications: Deep experience with Kubernetes, AWS, and Infrastructure-as-Code tools required.
The predicted salary is between 70000 - 90000 £ per year.
Our partner - a top tier Hedge Fund - keeps expanding AI workflows. We are looking for a platform infrastructure engineer to design, build, and operate cloud-native infrastructure for deploying AI workloads safely and reliably at scale.
Responsibilities
- The engineer will design container architectures for security-sensitive and multi-tenant environments.
- Implement network policies and access controls for workload isolation.
- Build CI/CD pipelines for reliable deployment.
- Establish infrastructure-as-code practices for reproducibility and auditability.
- Work closely with AI engineers, focusing on making the platform secure, scalable, and operationally excellent.
Skills
- Deep hands-on experience with Kubernetes (EKS preferred) — cluster design, networking (CNI, service mesh), RBAC, and security policies.
- Strong AWS expertise — VPC architecture, IAM, ECS/EKS, networking, and security groups.
- Proficiency with Infrastructure-as-Code tools such as Terraform, CloudFormation, or Pulumi.
- Experience designing container architectures for multi-tenant or security-sensitive workloads.
- Familiarity with GitOps workflows and CI/CD platforms (ArgoCD, GitHub Actions, Jenkins).
- BS + 5 years or MS + 3 years in a platform/infrastructure/DevOps engineering role.
- Python and/or Go for tooling and automation.
- Up-to-date with the latest advancements in cloud-native infrastructure, container security, and AI workload deployment.
Nice to have
- Familiarity with AI infrastructure — agent orchestration frameworks, MCP.
- Experience in the financial domain — regulated environments, compliance-aware infrastructure.
- Experience with container orchestration platforms for autonomous or long-running AI workloads.
- Prior experience securing production AI agent workloads at scale.
AI Platform Infrastructure Engineer employer: Luxoft
As a leading Hedge Fund, we pride ourselves on fostering a dynamic and innovative work environment where AI Platform Infrastructure Engineers can thrive. Our commitment to employee growth is evident through continuous learning opportunities and collaboration with top-tier AI engineers, all while working in a cutting-edge cloud-native infrastructure that prioritises security and scalability. Join us to be part of a forward-thinking team that values operational excellence and offers a unique chance to shape the future of AI workflows in the financial sector.
StudySmarter Expert Advice🤫
We think this is how you could land AI Platform Infrastructure Engineer
✨Tip Number 1
Network with industry professionals! Attend meetups, webinars, or conferences related to AI and cloud infrastructure. This is a great way to get your name out there and learn about job openings that might not be advertised.
✨Tip Number 2
Showcase your skills through personal projects or contributions to open-source. Build a portfolio that highlights your experience with Kubernetes, AWS, and Infrastructure-as-Code tools. This can really set you apart from other candidates!
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design questions. Focus on scenarios relevant to AI workloads and cloud-native infrastructure. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨Tip Number 4
Apply directly 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 AI Platform Infrastructure Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Kubernetes, AWS, and Infrastructure-as-Code tools. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
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 a perfect fit for our team. Keep it concise but impactful!
Showcase Your Projects:If you've worked on any cool projects related to cloud-native infrastructure or AI workloads, make sure to mention them. We love seeing real-world applications of your skills, so include links or descriptions where possible.
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’s super easy!
How to prepare for a job interview at Luxoft
✨Know Your Tech Inside Out
Make sure you’re well-versed in Kubernetes, AWS, and Infrastructure-as-Code tools. Brush up on your knowledge of cluster design, networking, and security policies. Being able to discuss these topics confidently will show that you’re the right fit for the role.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, especially related to cloud-native infrastructure and AI workloads. Use the STAR method (Situation, Task, Action, Result) to structure your answers and highlight how you tackled complex issues.
✨Familiarise Yourself with the Company’s Work
Research the hedge fund's AI initiatives and understand their approach to deploying AI workloads. This will not only help you tailor your responses but also demonstrate your genuine interest in their projects and how you can contribute.
✨Ask Insightful Questions
Prepare thoughtful questions about their current infrastructure challenges or future projects. This shows that you’re engaged and thinking critically about how you can add value to their team, especially in terms of security and scalability.
