Role Description As a Senior DevOps Consultant, you’ll be a key technical contributor in delivering complex projects — combining deep engineering skills with the confidence to work independently within your area of responsibility. You’ll take end-to-end ownership of your deliverables, ensuring they meet high standards of quality, security, and performance, while collaborating closely with colleagues and client teams to achieve project goals. - Apply modern DevOps practices to design, build, and optimise solutions that help clients get the most from their cloud platform. - Actively involved throughout the full project lifecycle — from refining requirements and influencing solutions, to delivering working systems and communicating outcomes to technical and non-technical audiences. - Provide guidance and informal mentoring to less experienced engineers, helping to raise capability within the team. - Contribute to pre-sales activities such as analysing technical requirements, working with our bid team, and helping develop compelling proposals. - Engage with Ensono Digital’s internal competencies — sharing knowledge, refining our delivery approaches, and expanding your own expertise. Qualifications - CI/CD & Automation - Infrastructure as Code & Cloud - Kubernetes, Containerisation & Networking - Security, Quality & Testing - Development & Debugging - Ways of Working & Collaboration - Emerging Practices Requirements - Designing and building advanced CI/CD pipelines from scratch using two or more platforms such as Azure DevOps, GitHub Actions, GitLab. - Creating reusable pipeline templates (e.g., Azure DevOps templates, GitHub Actions reusable workflows, and infrastructure modules (e.g., Terraform). - Integrating automated quality checks, testing, and security scanning into pipelines. - Hands-on commercial experience with at least one of the major cloud providers (AWS, Azure, or GCP). - Implementing Infrastructure as Code solutions using tools like Terraform, or cloud native tooling (ARM/Bicep, CloudFormation). - Designing, deploying, and operating Kubernetes clusters for production workloads at scale. - Configuring application routing using CDN, load balancers, and ingress controllers for single and multi-region architectures. - Knowledge of hub-and-spoke network architectures and their application in cloud environments. - Experience working with containerised applications hosted locally and on cloud native PaaS services – e.g. Azure Container Apps, AWS ECS Fargate. - Supporting security architecture and contributing to the definition of naming conventions, patterns, and practices. - Identifying and implementing build pipelines to validate non-functional requirements (e.g., performance, security, compliance). - Writing and maintaining tests for infrastructure code within an existing framework. - Analysing security scan results, particularly Common Vulnerabilities and Exposures (CVE) reports. - Debugging and troubleshooting applications in one or more languages such as Java, C#, or Node.js. - Preferred background in software development, with the ability to apply development principles and engineering practices. - Effectively resolving technical challenges on complex projects and delivering quality outcomes within your scope of work. - Strong communication skills, including presenting technical solutions, collaborating in cross-functional teams, and engaging with stakeholders. - Providing informal guidance and mentoring to less experienced engineers in the team. - Awareness of how Artificial Intelligence (AI) can accelerate project tasks such as documentation, refactoring, testing, and debugging. - Experience with AI-assisted development tools such as GitHub Copilot is desirable. Benefits - Highly competitive salary. - Prestigious sales and broader team recognition with Annual Presidents Club. - Company equity incentive plan. - 27 days annual leave + plus bank holidays (increasing to 30 with length of service). - ½ day leave for your birthday. - Sabbatical options at 5-years & 10-years’ service. - 5 days study leave. - 1 day charity leave to work for a charity of your choice. - Competitive pension. - Private healthcare for you and your family. - Enhanced parental leaves. - Life and income protection. - Payroll giving to your favorite charity. - Coaching & mentoring opportunities. - Additional perks such as discounted gym membership, cycle scheme, EAP and more!

• Design, build, and maintain highly available, scalable, and fault-tolerant systems • Collaborate with software engineering teams to ensure applications are designed with reliability and performance in mind • Develop and maintain automation procedures to maximize system efficiency, minimize human intervention, and optimize routine tasks • Monitor and analyze system performance to identify and address bottlenecks before they impact users • Ensure the infrastructure can handle rapid growth in web traffic and ML data processing • Participate in 24/7 on-call rotations (including scheduled shifts and holidays) • Practice sustainable on-call response, conduct root-cause analysis, and lead blameless post-mortems to prevent recurrence • Implement monitoring tools (SLIs/SLOs/SLAs) and set up automated alerting and metrics to track system health and performance • Implement and maintain security best practices and ensure all systems meet regulatory requirements

• Following SRE principles to maintain a 24/7 production environment running on Kubernetes • Implementation of DevOps methodologies to improve IT team quality of life • Proactive system monitoring and configuration • Incident response and postmortem processes • Managing and evolving AWS infrastructure (EKS, EC2, RDS, Fargate, CloudFront, Lambda, S3) • Building and maintaining CI/CD pipelines, infrastructure as code (Terraform, Helm, ArgoCD) • Ensuring system reliability, performance, and scalability across our production stack • Applying SRE discipline to ML infrastructure — ensuring model serving, training pipelines, and data systems are reliable, observable, and well-operated • Supporting and improving ML model deployment pipelines and MLOps practices • Monitoring ML model performance in production and building alerting and observability for ML systems • Collaborating with data scientists and product teams to operationalize ML models at scale • Contributing to infrastructure for ML workloads on Kubernetes and AWS

Title: Site Reliability Engineer Location: Chandler, AZ Duration: 12 months Work Engagement: W2 Work Schedule: Hybrid 3 days in office/2 days remote Benefits on offer for this contract position: Health Insurance, Life insurance, 401K and Voluntary Benefits Summary: In this contingent resource assignment, you may: Participate in low to moderately complex initiatives and identify opportunity for process improvements within Systems Operations Engineering. Review and analyze basic or tactical Systems Operations Engineering assignments or challenges that require research, evaluation, and selection of alternatives, related to low-to-medium risk deliverables. Present recommendations for resolving low to moderately complex situations and exercise some independent judgment while developing understanding of function, policies, procedures, and compliance requirements. Provide information to client personnel in Systems Operations Engineering. Required Qualifications: Systems Engineering experience, or equivalent demonstrated through one or a combination of the following: work or consulting experience, training, military experience, education. Key Requirements: · Applicants must be authorized to work for ANY employer in the U.S. This position is not eligible for visa sponsorship. Technical Skills • Experience supporting production applications or infrastructure. • ServiceNow or similar ITSM platform experience. • Experience working with monitoring and observability tooling. • Unix/Linux and Windows fundamentals. • Experience troubleshooting application and batch processing issues. • Understanding of change, incident, and problem management processes. Automation Skills • Basic coding or scripting knowledge in one or more of: o PowerShell o Python o Shell scripting o Low-code automation platforms • Ability to modify, validate, and execute automation workflows. • Willingness to continue developing automation and AI skills. Reliability Engineering Fundamentals • Basic understanding of monitoring and alert management. • Analytical approach to troubleshooting and problem solving. • Understanding of operational risk and production support practices. • Interest in reliability engineering and continuous improvement.