Platform Engineer - Cloud Engineering

ebp Global is a high-performing boutique consultancy firm best known for delivering tailored, impactful solutions to our clients’ most complex problems, from conceptualisation to implementation. Our expertise covers a wide range of value chain activities from strategy, organisational design and operating models, through operations and business process optimisation, to information flows and analytics. It is through our hands-on approach, and deep knowledge that we are proud to claim some of the world’s most well-known companies, across a wide variety of industries as long-term client partners.

We are seeking a highly skilled and experienced Cloud Platform Engineer with expertise in Azure and AWS to join our dynamic IT team. The ideal candidate will be responsible for designing, implementing, and managing our cloud architecture and infrastructure, ensuring the highest levels of availability, performance, and security. Critical and conceptual thinking and problem-solving skills are essential alongside passion for networking.

• Design and implement scalable and secure network architectures in both Azure and AWS environments.
• Plan and execute cloud migration strategies, including hybrid cloud solutions.
• Design infrastructure for AI/ML workloads including GPU/TPU compute clusters, high-throughput storage, and low-latency networking between nodes.
• Architect MLOps pipelines integrating model training, versioning, and deployment workflows on cloud platforms (e.g., Azure ML, AWS SageMaker).
• Deploy and manage virtual networks, subnets, route tables, and network gateways.
• Implement and manage VPN connections, Direct Connect (AWS), and ExpressRoute (Azure).
• Deploy and manage AI-specific services such as AWS SageMaker, Azure Machine Learning, and GPU-enabled VM fleets.
• Set up and manage vector databases.
• Configure and manage API Gateways (AWS API Gateway, Azure API Management) for routing, throttling, and versioning.
• Ensure cloud infrastructure adheres to industry standards and regulatory requirements.
• Implement data governance and access controls for sensitive training datasets and model artifacts.
• Ensure compliance with AI-specific regulations and responsible AI frameworks (e.g., EU AI Act considerations).
• Monitor network performance and implement tuning measures to optimize throughput and latency.
• Troubleshoot and resolve network-related issues promptly.
• Conduct capacity planning and scaling to accommodate growing workloads.
• Automate deployment, configuration, and management tasks using scripting languages such as Python, PowerShell, or Bash.
• Build and maintain CI/CD pipelines for model deployment using tools like MLflow, Kubeflow, or Azure DevOps.
• Automate model retraining triggers, A/B deployment rollouts, and blue/green model switches.
• Experience deploying Python-based REST APIs using frameworks such as FastAPI or Flask.
• Build CI/CD pipelines for automated testing, containerization, and deployment of Python APIs to cloud environments.
• Support LLM and generative AI deployments including API gateway configuration for models like Azure OpenAI or AWS Bedrock.
• Manage prompt caching layers, rate limiting, and cost monitoring for AI API consumption.
• Collaborate with data science and AI teams to translate model requirements into scalable cloud infrastructure.
• Provide technical guidance and support to junior network engineers and other team members.
• Design, deploy, and manage RESTful APIs built in Python (FastAPI, Flask, or Django REST Framework).
• Monitor API performance, uptime, and error rates using tools like CloudWatch, Azure Monitor, or Datadog.
• Manage API monetization or access tiers where applicable, using gateway-level policies.

Key Skills for a Cloud Platform Engineer:

• Minimum of 5 years of experience in network engineering, with at least 3 years focused on cloud environments.
• Proven experience designing and managing network infrastructure in both Azure and AWS.
• Bachelor's degree in Computer Science, Information Technology, or a related field.
• AWS Certified Solutions Architect – Professional or AWS Certified Advanced Networking – Specialty.
• AWS Certified Machine Learning – Specialty.
• Microsoft Certified: Azure AI Engineer Associate.
• Relevant network certifications (e.g., Cisco CCNA/CCNP).
• Proficiency with Python REST API development and deployment (FastAPI, Flask).
• Hands-on experience with AWS API Gateway or Azure API Management (APIM).
• Ability to learn and upgrade technical skills, in the fast-paced data analysis field.
• Ability to work in a dynamic, agile environment within a geographically distributed team.

Remote, flexible working environment.

Please apply by sending your CV (in English) to info@ebp-global. Personal data collected will be used for recruitment purpose only.