ABOUT US:

We are an engineering consultancy bridging Quality Engineering, Cloud Platforms and Developer Experience.
Our values challenge us to do the best we can for ClearRoute, our customers and most importantly our team. We want to create a collaborative team to help build ClearRoute. This is an opportunity for you to build a consultancy from the ground up, use your voice to drive change and help transform organisations and problem domains.

REQUIRED EXPERIENCE:

• Strong experience with Microsoft Azure, including Azure Machine Learning, Azure Databricks, Azure Data Factory, and Azure Kubernetes Service (AKS).
• Proficiency in programming languages such as Python, C#, or Java.
• Solid understanding of AI/ML workflows, MLOps, and data pipelines.
• Proven track record in building and deploying AI platforms at scale.
• Experience with CI/CD tools like Azure DevOps, Jenkins, or GitHub Actions.
• Ability to troubleshoot complex technical challenges in a cloud environment.
• Excellent communication, teamwork, and the ability to explain complex technical concepts to non-technical stakeholders.

PREFERRED SKILLS:

• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch).
• Familiarity with data governance and compliance (e.g., GDPR, HIPAA).
• Knowledge of Infrastructure as Code (IaC) using tools like Terraform or ARM templates.

ROLE:

We are seeking a highly skilled and motivated AI Platform Engineer (Senior Quality Cloud Engineer) to join our dynamic team. If you are passionate about building scalable AI platforms and have hands-on experience with Microsoft Azure’s suite of tools and services, this is your opportunity to make a significant impact. You will design, deploy, and maintain AI and machine learning platforms that empower teams to develop cutting-edge solutions, driving business innovation and success.

KEY RESPONSIBILITIES:

• Design & Implementation: Architect and build robust AI and machine learning platforms using Azure tools, ensuring scalability, reliability, and security.
• Integration: Integrate Azure Machine Learning, Databricks, and other Azure services into a seamless AI ecosystem.
• Automation: Develop CI/CD pipelines for AI/ML workflows, leveraging tools like Azure DevOps.
• Collaboration: Work closely with data scientists, data engineers, and software developers to optimize model deployment and inference.
• Optimisation: Monitor and fine-tune system performance, ensuring efficient resource utilization on Azure.
• Security & Compliance: Implement best practices for securing AI workflows and ensuring compliance with industry standards.