Jobs at CUBE (Now Hiring) — 29 open — Page 2

CUBE are a global RegTech business defining and implementing the gold standard of regulatory intelligence for the financial services industry. We deliver our services through intuitive SaaS solutions, powered by AI, to simplify the complex and everchanging world of compliance for our clients.

Why us?

🌍 CUBE is a globally recognized brand at the forefront of Regulatory Technology. Our industry-leading SaaS solutions are trusted by the world’s top financial institutions globally.

🚀 In 2024, we achieved over 50% growth, both organically and through two strategic acquisitions. We’re a fast-paced, high-performing team that thrives on pushing boundaries—continuously evolving our products, services, and operations. At CUBE, we don’t just keep up we stay ahead.

🌱 We believe our future is built by bold, ambitious individuals who are driven to make a real difference. Our “make it happen” culture empowers you to take ownership of your career and accelerate your personal and professional development from day one.

🌐 With over 700 CUBERs across 19 countries spanning EMEA, the Americas, and APAC, we operate as one team with a shared mission to transform regulatory compliance. Diversity, collaboration, and purpose are the heartbeat of our success.

💡 We were among the first to harness the power of AI in regulatory intelligence, and we continue to lead with our cutting-edge technology. At CUBE, You will work alongside some of the brightest minds in AI research and engineering in developing impactful solutions that are reshaping the world of regulatory compliance.

Purpose

This role focuses on cloud-native platform engineering: building self-service infrastructure, standardised deployment patterns, and reliable runtime platforms on Azure. You will work closely with software, data, and ML teams to provide guardrails, automation, and operational excellence across the full system lifecycle.

Key Responsibilities

• Design, build, and operate shared platform services on Microsoft Azure, with a strong focus on AKS-based runtime platforms.
• Develop and maintain reusable infrastructure and platform modules (Terraform, Helm) that enable safe self-service by application, data, and ML teams.
• Own platform components end-to-end (build–run), including availability, performance, security, cost, and operability.
• Define and evolve platform standards and golden paths for workload onboarding, networking, identity, secrets, observability, and scaling.
• Implement infrastructure and platform changes using Infrastructure as Code (Terraform) and GitOps-style workflows.
• Contribute to and improve CI/CD pipelines using Azure DevOps and GitHub Actions, including automated validation, approvals, and rollbacks.
• Reduce manual operational effort through automation, self-service tooling, and opinionated defaults.
• Ensure platform services meet agreed SLOs, security controls, compliance requirements, and resilience standards.
• Implement and maintain observability using New Relic, including metrics, logs, alerts, and dashboards.
• Lead or support investigation and resolution of complex platform incidents; contribute to post-incident reviews and systemic improvements.
• Design and validate backup, recovery, and disaster recovery mechanisms for platform-managed services.
• Enable application teams with reliable deployment and runtime patterns (e.g. ingress, service mesh, secrets, scaling, CI/CD integration).
• Support DataOps and MLOps workloads by providing secure, scalable platforms for data pipelines, model training, and inference.
• Collaborate with data and AI teams on services such as Microsoft Fabric, data platforms, and ML lifecycle tooling.
• Act as a senior technical partner to software engineers, data engineers, and ML engineers.
• Provide technical input into solution and service design, ensuring operational and platform considerations are addressed early.
• Mentor and support junior and mid-level engineers, sharing platform engineering best practices.
• Contribute to continuous improvement of platform processes, documentation, and standards.

Skills & Competencies

• Strong experience in cloud engineering, with hands-on expertise in Microsoft Azure.
• Production experience operating Azure Kubernetes Service (AKS) at scale.
• Advanced use of Terraform for infrastructure and platform provisioning (modules, state management, governance).
• Strong working knowledge of Helm for Kubernetes workload and platform configuration.
• Experience building and operating CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Solid understanding of cloud networking, identity (Azure AD / Managed Identity), private endpoints, and security controls.
• Experience designing self-service platforms or reusable infrastructure patterns.
• Strong understanding of reliability engineering, incident management, and change control in production environments.
• Practical experience with observability and monitoring, ideally with New Relic or equivalent tools.
• Ability to balance delivery speed with risk management, stability, and long-term sustainability.
• Clear communicator, able to explain technical trade-offs and risks to both technical and non-technical stakeholders.
• Comfortable working autonomously within a defined platform scope.
• Strong sense of ownership and accountability for platform outcomes.
• Exposure to DataOps or MLOps practices, tooling, or platforms.
• Experience supporting data pipelines, lakehouse architectures, or ML workloads on cloud platforms.
• Familiarity with Microsoft Fabric, ML pipelines, model deployment, or feature stores.

Required Experience & Qualifications

• Relevant experience, training, or demonstrated capability for the role's track, domain, and level.
• Practical understanding of the tools, methods, governance, and delivery practices used in the role.
• Ability to work effectively with relevant stakeholders and contribute to reliable, high-quality outcomes.
• Relevant degree, professional qualification, certification, apprenticeship, or equivalent experience is desirable where applicable.

Performance Indicators

• High availability and reliability of platform services used by delivery teams.
• Safe, repeatable, and automated platform changes with minimal unplanned incidents.
• Improved developer, data, and ML team experience through self-service and standardisation.
• Reduction in platform-related incidents, toil, or technical debt over time.
• Positive feedback from engineering teams on platform usability and support.

Interested?

If you are passionate about leveraging technology to transform regulatory compliance and meet the qualifications outlined above, we invite you to apply. Please submit your resume detailing your relevant experience and interest in CUBE.

CUBE is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.