Location
London

Hours
Full Time

Salary
Competitive salary package

About the Role
Allwyn Lottery Solutions is a global leader in digital lottery and gaming solutions, part of the Allwyn Entertainment Group with a strong presence across Europe. Our mission is to enhance player experiences through cutting-edge technology that drives engagement and maximizes returns for good causes. Our flagship platform, Genesis, supports lotteries worldwide with secure player account management, draw-based games, instant games, and modern web and mobile applications.

The Business Intelligence & Data team builds platforms that transform data into valuable insights powering analytics, AI, and customer-facing applications. As a Cloud Platform Engineer, you will design, build, and operate a modern AWS cloud platform supporting large-scale data processing, machine learning, APIs, and web applications. Working collaboratively with Data Engineers, Developers, Data Scientists, and Architects, you will deliver secure, scalable, and automated cloud solutions focused on reliability, performance, and innovation.

This role involves AWS platform engineering, cloud networking, security, automation, serverless architecture, observability, and application platform operations. You will help evolve our cloud-native platform ensuring operational excellence, security, performance, and governance across data services and products.

Key Responsibilities
- Design, build, and operate cloud infrastructure and platform services supporting data platforms, AI/ML services, APIs, and web applications
- Develop reusable infrastructure patterns and automation using Infrastructure as Code
- Build and optimize cloud-native, serverless, and event-driven architectures
- Design and maintain secure, resilient cloud networking and connectivity
- Implement and improve security controls including IAM, encryption, secrets management, and threat detection
- Design and maintain CI/CD and GitOps workflows for infrastructure and applications
- Partner with Product Engineers to provide hosting, deployment, observability, scaling, and operational capabilities
- Implement monitoring, logging, alerting, and operational tooling to ensure platform health and availability
- Support deployment and operation of machine learning and AI-powered services
- Investigate and resolve complex infrastructure, networking, security, and platform issues
- Identify opportunities to improve automation, reliability, security, performance, scalability, and cost efficiency

Experience
- Minimum 5 years in Platform Engineering, Cloud Engineering, DevOps, Site Reliability Engineering, Data Platform Engineering, or similar roles
- Strong hands-on experience designing, building, and operating production workloads on AWS including serverless, event-driven, and containerized architectures
- Solid understanding of AWS infrastructure, networking, and security including routing, DNS, load balancing, TLS, network segmentation, VPN, IAM, encryption, secrets management, vulnerability management, perimeter protection, and security monitoring
- Experience supporting data engineering, analytics, business intelligence, and reporting platforms within AWS
- Proficiency with Infrastructure as Code tools (Terraform, OpenTofu, Ansible, or similar), automation using Python and/or Node.js
- Experience implementing CI/CD pipelines, GitOps workflows, and modern cloud deployment practices
- Strong knowledge of observability, monitoring, alerting, incident response, and troubleshooting complex infrastructure and deployment issues

About You
- Strong analytical and problem-solving skills with ability to diagnose complex technical issues and drive solutions
- Self-motivated, proactive, and comfortable working in a fast-paced, lean environment
- Systems-thinking mindset capable of designing and optimizing end-to-end platform architectures
- Strong security awareness and understanding of operational risk, compliance, governance, and engineering best practices
- Excellent collaboration, communication, and documentation skills
- Passionate about automation, continuous improvement, engineering excellence, and staying current with emerging cloud and AI technologies

Qualifications
- Degree in Computer Science, Information Technology, Engineering, or equivalent practical experience
- Excellent verbal and written communication skills with strong command of English
- Desired: Experience supporting machine learning workloads or MLOps, modern data lake and streaming architectures, AWS cost optimisation and FinOps principles, operating in regulated or high-availability environments
- Desired: Experience with test automation frameworks such as PyTest, UnitTest, Vitest, Jest, or similar
- Desired: AWS certifications in Architecture, DevOps, Security, Networking, Data, or Machine Learning