Cloud DevOps Engineer (AWS)
Build the backbone of an AI-powered global risk intelligence platform
We are building something ambitious.
Our AI platform ingests global risk data, supports machine learning pipelines, and delivers real-time intelligence to executive and operational decision-makers. We are now looking for a Cloud DevOps Engineer to architect and scale the infrastructure that powers it.
This is not a maintenance role.
This is a build-and-scale role.
You will design the cloud foundation for a multi-tenant SaaS platform operating in high-availability, high-trust environments.
What You’ll Be Building
• A secure, multi-tenant AWS architecture designed for scale
• Production-grade ML infrastructure powering AI inference
• Fully automated CI/CD pipelines
• Observability systems providing real-time operational insight
• Infrastructure-as-Code environments built for speed and reliability
You’ll work closely with our AI engineers, security specialists, and product team to turn advanced models into robust, production-ready systems.
Your Impact
You will:
• Design, implement and manage AWS-based infrastructure using Infrastructure as Code
• Build resilient, scalable multi-tenant SaaS architecture
• Develop and optimise CI/CD pipelines for rapid, secure deployments
• Implement observability across infrastructure and services (metrics, logs, alerts)
• Enable ML teams with scalable compute for training and inference
• Drive uptime, performance, and reliability standards
• Embed security best practices across the cloud environment
• Help shape the technical direction of our platform as we scale
Technical Environment
Cloud: AWS (VPC, EC2, S3, Lambda, EKS, SNS, SQS)
Containers: Kubernetes, Docker, Helm
IaC: CloudFormation, CDK, Terraform
CI/CD: Azure DevOps (or equivalent)
Monitoring: Prometheus, Grafana
Languages: Python, Bash
Experience running ML workloads in production environments is highly valued.
What We’re Looking For
• Strong experience as a DevOps or Cloud Engineer
• Experience in multi-tenant SaaS environments
• Deep understanding of AWS architecture and networking
• Strong containerisation & orchestration knowledge
• Infrastructure-as-Code mindset
• CI/CD pipeline design experience
• Experience supporting ML/AI production workloads
• A bias toward automation and reliability
• Security-first thinking
Why This Role Is Different
• You’ll influence architecture from the ground up
• You’ll work on AI systems with real-world operational impact
• You’ll operate in a fast-scaling, high-ambition environment
• You’ll help build infrastructure that leadership teams rely on
This is a rare opportunity to combine cloud engineering, AI infrastructure, and mission-driven technology in one role.
Growth
As we scale, this role can evolve into:
• Lead Cloud Architect
• Head of Platform Engineering
• DevOps Team Lead
We are building for scale — and we want someone who wants to scale with us.
