AI Platform Engineer

Huxley; Brussel; On-site; EUR 100,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Continued learning stipend

Job summary

Huxley is seeking a Senior AI Platform Engineer to design, build, and operate the cloud-native platform that powers AI workloads. The role collaborates with architects, security, and data teams to ensure a scalable, secure, and observable platform.

The engineer will own platform reliability, automation, and governance, shaping standards for AI deployments and enabling self-service capabilities for AI teams.

Qualifications

• Bachelor’s or Master’s degree in CS, Engineering, IT, or equivalent practical experience.
• Proven experience in platform engineering, DevOps, SRE, or cloud infrastructure roles.
• Hands-on experience operating cloud platforms in enterprise environments.
• Strong hands-on experience with AWS.
• Solid experience managing Kubernetes environments in production.
• Experience implementing Infrastructure-as-Code with Terraform.
• Experience building and maintaining CI/CD pipelines.
• Good understanding of cloud networking, security, and infrastructure architecture.
• Experience with Docker and container technologies.
• Scripting and automation using Python, Bash, or similar.

Responsibilities

• Design, implement, and operate cloud-native platform services for AI workloads.
• Build and maintain scalable Kubernetes environments.
• Manage infrastructure using IaC practices.
• Improve platform reliability, resilience, and performance.
• Ensure platform availability through monitoring, automation, and best practices.
• Develop and maintain CI/CD pipelines for platform and app deployments.
• Automate infrastructure provisioning and operational processes.
• Enable self-service capabilities for engineering and AI teams.
• Promote DevOps practices and engineering excellence across teams.
• Implement secure-by-design principles across the platform.

Skills

Cloud platform engineering

DevOps

Site Reliability Engineering

Kubernetes

Terraform

CI/CD

Python scripting

Docker

Security

Communication

Education

Bachelor’s or Master’s degree in Computer Science, Engineering, IT, or related field

Tools

AWS

Kubernetes

Terraform

Docker

Job description

Build the platform that powers the next generation of AI solutions

Our client is a leading organization undergoing a large-scale digital and AI transformation. With ambitious plans to accelerate the adoption of Artificial Intelligence across the business, they are investing in a modern cloud-native platform that enables the secure, scalable, and efficient deployment of AI-powered solutions.

To support this journey, we are looking for a Senior AI Platform Engineer who will play a key role in designing, building, and operating the infrastructure and platform capabilities that will enable AI teams to innovate at scale.

If you're passionate about cloud technologies, platform engineering, automation, and emerging AI ecosystems, this is an opportunity to have a direct impact on the future of enterprise AI.

Your Role

As a Senior AI Platform Engineer, you will be responsible for building and maintaining the technical foundation that supports AI and Generative AI initiatives across the organization.

You will work closely with architects, security teams, software engineers, data professionals, and AI specialists to ensure that the platform is scalable, secure, reliable, and aligned with enterprise standards.

This is a hands-on engineering role with significant influence over architecture decisions, technology standards, operational excellence, and platform strategy.

Key Responsibilities

Platform Engineering & Cloud Infrastructure

• Design, implement, and operate cloud-native platform services supporting AI workloads.
• Build and maintain scalable Kubernetes environments.
• Manage infrastructure using Infrastructure-as-Code practices.
• Improve platform reliability, resilience, performance, and scalability.
• Ensure platform availability through monitoring, automation, and operational best practices.

Automation & DevOps

• Develop and maintain CI/CD pipelines for platform and application deployments.
• Automate infrastructure provisioning and operational processes.
• Enable self-service capabilities for engineering and AI teams.
• Promote DevOps practices and engineering excellence across teams.

Security & Governance

• Implement secure-by-design principles across the platform.
• Manage identity, authentication, authorization, and access control mechanisms.
• Collaborate with cybersecurity teams to ensure compliance with internal and regulatory standards.
• Contribute to governance frameworks, operational controls, and platform policies.

AI Enablement

• Provide the infrastructure and platform capabilities required for AI and Generative AI use cases.
• Partner with AI and data teams to support model deployment and operationalisation.
• Evaluate and integrate emerging AI ecosystem technologies where appropriate.
• Help establish standards and best practices for AI platform operations.

Monitoring & Operations

• Implement observability, monitoring, logging, and alerting solutions.
• Troubleshoot complex infrastructure and platform issues.
• Continuously optimise platform performance, cost efficiency, and user experience.
• Participate in platform lifecycle management and continuous improvement initiatives.

What We’re Looking For

• Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology, or equivalent practical experience.
• Strong experience in Platform Engineering, DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure roles.
• Proven experience operating cloud platforms in enterprise environments.
• Strong hands-on experience with AWS.
• Solid experience managing Kubernetes environments in production.
• Experience implementing Infrastructure-as-Code solutions using Terraform.
• Experience building and maintaining CI/CD pipelines.
• Good understanding of cloud networking, security, and infrastructure architecture.
• Experience with container technologies such as Docker.
• Scripting and automation experience using Python, Bash, or similar technologies.
• Strong troubleshooting, analytical, and problem-solving skills.
• Ability to communicate effectively with both technical and non-technical stakeholders.