AI Platform Engineer

Huxley; Brussel Hoofdstad; Hybrid; EUR 90,000 - 130,000; Full time

Job summary

Huxley is seeking a Senior AI Platform Engineer to design, build and operate the secure cloud-native foundation for AI initiatives. You will partner with architects, security, data, and AI teams to ensure a scalable, reliable platform across enterprise environments.

The role emphasizes hands-on engineering, architecture decisions, and governance to enable AI and Generative AI deployments with modern automation and observability practices.

Qualifications

• Solid hands-on experience in platform engineering and cloud infrastructure.
• Experience with AWS and production Kubernetes environments.
• Experience with Infrastructure-as-Code using Terraform.
• Scripting proficiency in Python or Bash.

Responsibilities

• Design, build, and operate cloud-native platform services for AI workloads.
• Manage scalable Kubernetes environments and IaC workflows.
• Develop CI/CD pipelines and automation for platform deployments.
• Ensure security, governance, and identity access controls on the platform.
• Collaborate with AI, data, and security teams to enable AI initiatives.
• Monitor, troubleshoot, and optimize platform performance and cost.

Skills

Platform Engineering

DevOps

SRE

Cloud Infrastructure

AWS

Kubernetes

CI/CD

Python

Bash

Docker

Education

Bachelor's or Master's in CS/Engineering/IT

Tools

Terraform

Kubernetes

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 operationalization.
• 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 optimize 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.

To find out more about Huxley please visit www.huxley.com