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Cloud Engineer (AI & Infrastructure) — evoke (Leeds, UK)
About Us
evoke (formerly 888 Holdings) is a global leader in sports betting, gaming, and digital entertainment, powering iconic international brands including William Hill, 888, and Mr Green. Headquartered with key technology hubs in Leeds, evoke is driven by a new strategic direction focused on technological innovation, customer safety, and world-class digital experiences.
Our technology division builds scalable, high-concurrency platforms that process millions of daily transactions while pioneering responsible gambling systems and cutting-edge artificial intelligence platforms.
Website: https://www.evokeplc.com/
Job Overview & Key Responsibilities
As a Cloud Engineer (AI Focus) on a 3–6 Month Fixed Term Contract, you will join a newly formed, specialized engineering squad at evoke in Leeds. Working within a hybrid model (80% remote, 20% in-office for team collaboration), you will design, deploy, and maintain the cloud infrastructure powering evoke’s next-generation Machine Learning and Agentic AI platforms on Amazon Web Services (AWS).
Key Responsibilities
- AI Platform Architecture: Build, optimize, and maintain scalable cloud infrastructure for core Machine Learning platforms and Agentic AI systems using AWS Bedrock, SageMaker, and AWS AgentCore.
- Infrastructure as Code (IaC) & Orchestration: Provision, manage, and scale cloud-native services using IaC tools and container orchestration engines centered on Kubernetes.
- System Observability & Reliability: Implement automated monitoring, logging, and observability standards to guarantee high availability and platform resilience across distributed cloud environments.
- Cross-Functional Collaboration: Partner closely with platform engineers, data scientists, and software teams to integrate third-party AI APIs and internal microservices seamlessly.
- 24/7 Operational Support: Participate in an on-call support rotation to ensure continuous operational excellence, rapid incident response, and service availability.
Requirements & Desired Qualifications
- Cloud Expertise: Demonstrated track record in a Cloud, Platform, or DevOps Engineering role, featuring advanced expertise in AWS cloud services.
- AI/ML Infrastructure: Practical familiarity with cloud AI frameworks, including Amazon SageMaker, Amazon Bedrock, and Agentic AI orchestrators.
- Containerization & IaC: Strong proficiency with Kubernetes management alongside automated infrastructure provisioning tools (e.g., Terraform, CloudFormation).
- Distributed Systems: Solid grasp of cloud-native architecture, microservice networking, security protocols, and high-concurrency cloud environments.
- Mission Alignment: Commitment to maintaining responsible gambling values, platform security, and data integrity.
Job Role Comparison Table
| Feature / Aspect | Traditional DevOps Engineer | Cloud Engineer – AI (evoke) | Machine Learning Engineer |
| Primary Focus | General CI/CD pipelines & web server hosting | AI/ML cloud infrastructure & Agentic AI platforms | Model architecture, feature engineering & model training |
| Core AWS Stack | EC2, S3, VPC, IAM, EKS | Amazon Bedrock, SageMaker, EKS, AgentCore | SageMaker, PyTorch, TensorFlow, MLflow |
| Contract & Work Model | Permanent / Full-time | 3–6 Month FTC (Hybrid: 80% Remote / 20% Office) | Permanent / Full-time |
| Domain Application | Standard web application hosting | Gaming, high-volume betting & Agentic AI platforms | Predictive analytics & recommendation engines |
Key Benefits of This Role
- Flexible Hybrid Working: Enjoy working from home 80% of the time, spending just 20% in evoke’s modern Leeds office for team coffee and collaborative sessions.
- Next-Gen AI Exposure: Get hands-on experience building foundational Agentic AI and enterprise LLM platforms in a high-scale commercial setting.
- Competitive Perks & Bonuses: Access to financial performance bonuses, high-street retailer discounts, and competitive pension contributions.
- Health & Wellness Benefits: Discounted gym memberships, Cycle to Work scheme, and mental health resources via employee support platforms.
- Inclusive Family Policies: Industry-leading maternity and paternity leave frameworks alongside supportive policies for carers.
How to Prepare a CV for This Position
- Highlight AWS & AI Services Prominently: Put cloud credentials (e.g., AWS Certified Solutions Architect, AWS Machine Learning Specialty) and specific tools (Bedrock, SageMaker, Kubernetes) at the top of your technical summary.
- Showcase IaC & Automation Skills: Explicitly detail how you have used Terraform, CloudFormation, or Ansible to automate infrastructure provisioning.
- Quantify Scalability & Impact: Use concrete metrics (e.g., “Deployed Kubernetes clusters supporting 50k+ daily active users with 99.99% uptime”).
- Detail On-Call & Reliability Experience: Demonstrate experience managing high-concurrency production systems, incident response workflows, and SLA management.
Career Guide Tips for Growth
- Deepen Knowledge of Agentic Frameworks: Study emerging Agentic AI architectures, tool-use patterns, and frameworks like AWS AgentCore and LangChain to position yourself as an expert in generative AI infrastructure.
- Master Cloud Observability for ML: Gain expertise in tracking LLM latency, token usage, and model drift using observability platforms like Datadog, Prometheus, and AWS CloudWatch.
- Build Multi-Cloud & Security Hygiene: Combine infrastructure automation with strict security measures (IAM roles, least-privilege policies, and data encryption) to excel in regulated industries like gaming and finance.
How to Prepare for the Interview
- Review the Hiring Journey: Expect a 3-stage process starting with an Initial Screening Call, followed by a Technical Round and a final culture-fit conversation.
- Be Ready for System Design: Practice designing cloud architectures for hosting large language models and Machine Learning pipelines on AWS under high-traffic constraints.
- Demonstrate Responsible Gaming Alignment: Familiarize yourself with evoke’s core brands (William Hill, 888, Mr Green) and express a clear understanding of the importance of platform reliability and customer protection in gaming.
Interview Questions & Guidance
1. “How would you design a scalable AWS infrastructure to deploy an LLM-powered Agentic application using Amazon Bedrock and Kubernetes?”
How to answer: Outline an end-to-end architecture: using EKS for microservice orchestration, AWS Bedrock API endpoints for LLM inferencing, IAM roles for service authentication, ElastiCache for conversation state management, and CloudWatch/Prometheus for latency monitoring.
2. “How do you manage infrastructure drift and ensure security compliance when deploying automated Kubernetes clusters via Infrastructure as Code?”
How to answer: Explain using GitOps workflows (e.g., ArgoCD/Flux) alongside Terraform for state enforcement. Mention automated security scans (e.g., Trivy, Checkov) integrated into CI/CD pipelines to prevent misconfigurations prior to deployment.
3. “Can you describe a time when you managed a production incident while on call? How did you restore service and prevent recurrence?”
How to answer: Frame using the STAR method: explain the immediate triage steps (checking metrics, rolling back faulty releases), clear stakeholder communication, and the post-mortem process that identified root causes and introduced automated preventative alerts.
Salary Insight
- Contract Type: 3–6 Month Fixed Term Contract (37.5 hours per week).
- Estimated Market Rate: Cloud Engineers specializing in AWS AI/ML infrastructure in the Leeds area typically command pro-rata compensation ranging between £65,000 – £85,000 per annum (or competitive daily contract rates depending on engagement terms).
- Work Arrangement: Hybrid working (80% remote, 20% Leeds office).
How to Apply
To apply for the Cloud Engineer (AI Focus) position at evoke:
- Online Application: Submit your CV directly via the official evoke career portal (
careers.evokeplc.com) or designated UK tech job channels. - Office Location: Leeds, West Yorkshire, United Kingdom (Hybrid model).
- Selection Steps: Initial CV screening, introductory talent call, and a technical engineering interview stage.
Career Page Link: Career Website
Disclaimer
This job summary and interview guide has been independently created for career preparation and recruitment informational purposes. evoke (888 Holdings PLC) retains all primary rights to its job listings, brand assets, and hiring decisions. Applicants should verify contract terms, salary specifics, and working arrangements directly through official evoke recruitment representatives.