CloudOPS (SME)

CloudOPS (SME) 

Our enterprise clients are moving from fragmented data foundations to AI-first data platforms capable of supporting large-scale, business-critical AI systems.
AI performance is directly constrained by data quality, availability, governance, and latency.

This role exists to build and operate the data backbone that enables reliable, scalable, and compliant AI at enterprise scale.

____________________________________________________________
 

Mission 

You will operate as a Subject Matter Expert in complex enterprise environments, designing and delivering AI-ready data platforms where reliability, scalability, lineage, and governance are non-negotiable.

Acting in consultative client engagements, outsourced delivery, or product-based models, you will own the end-to-end lifecycle of data pipelines, from ingestion to serving, while acting as a technical authority on data engineering for AI systems.

 

Key Responsibilities

AI Infrastructure (Core)

• Design and operate compute platforms for AI workloads (CPU, GPU, accelerators)

• Manage hybrid and cloud-based AI infrastructures

• Ensure high availability, resilience, and performance of AI platforms

• Plan and manage capacity for training and inference workloads
   

Cloud, Data Center & Platform Operations

• Operate containerized and virtualized environments supporting AI systems

• Manage storage and networking optimized for data-intensive workloads

• Implement observability, monitoring, and incident response for AI platforms

• Ensure operational readiness and 24/7 reliability where required
   

Cost, Performance & Scalability

• Optimize infrastructure for cost, throughput, and latency

• Implement FinOps practices for AI compute and storage

• Balance performance requirements with budget and sustainability constraints

• Support scaling strategies from POC to enterprise-wide deployment

 

Technical Scope

Infrastructure Stack

• Cloud platforms (public, private, hybrid)

• On-prem data centers and hybrid extensions

• GPU scheduling and accelerator management

• High-performance storage and networking
   

Platform & Operations

• Container orchestration (Kubernetes or equivalent)

• Infrastructure as Code

• Monitoring, logging, alerting systems

• Backup, disaster recovery, and resilience patterns
   

Production Awareness

• SLA-driven operations

• Security and compliance alignment with infrastructure design

• Close collaboration with AI/ML, Data, DevOps, and Security teams

Profile

Experience

• Strong background in infrastructure, cloud, or platform operations

• Experience operating high-performance or data-intensive systems

• Exposure to AI or ML workloads in production environments
   

Mindset

• Operations-driven engineering mindset

• Strong sense of ownership and accountability

• Comfortable operating under reliability and performance constraints

• Continuous improvement approach to scalability and cost efficiency
   

___________________________________________________________

This is not a traditional infrastructure role.

This role is designed to power enterprise AI systems at scale, acting as the compute and platform backbone for advanced AI initiatives.

You will position yourself as an AI Infrastructure SME, enabling AI platforms to scale by orders of magnitude, and contributing to the build-out of one of the most robust AI compute ecosystems across Europe.