AI Job Summary

Design, implement and manage AWS infrastructure using CloudFormation, CDK, and Terraform.
Build resilient, scalable multi-tenant SaaS architecture on AWS (VPC, EC2, S3, Lambda, EKS, SNS, SQS).
Support ML/AI production workloads including infrastructure for training and inference.

Role Type

Permanent • Full-time • Mid-level Senior

Description

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.

Cloud DevOps Engineer (AWS)

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Cloud DevOps Engineer (AWS)

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