Software Engineering Practitioner

In the role of Software Engineering Practitioner, you will play a critical role in building and sustaining the engineering foundations that underpin our technology estate. Your work ensures platforms, applications, and operational tooling are secure, resilient, observable, and aligned with enterprise architecture strategy and engineering principles.

This role is critical to ensuring the organisation can deliver at pace with confidence, reliability, and resilience. By building and maintaining fit‑for‑purpose platforms, embedding strong engineering and documentation practices, and enabling automation, monitoring, and testing, the role reduces operational risk and improves service quality. Ownership of key operational capabilities—including security controls, application support, and incident readiness—helps proactively detect and resolve issues, protect customers, and safeguard the organisation’s reputation. Through continuous improvement, robust standards, and accessible, reusable knowledge, the role strengthens auditability, organisational resilience, and long‑term sustainability.

What you’ll be doing

• Implement practical engineering solutions, platform standards, and automation using architecture.
• Translate architectural, security, and operational requirements into reusable engineering patterns.
• Enable consistent ways of working across engineering, operations, and support teams.
• Develop custom scripts, APIs, and integrations to extend platform capabilities.
• Build & enable Dynatrace dashboards, metrics, and reporting to support engineering, operations and application support.
• Support and enable testing strategies, frameworks, and automation across applications and platforms.
• Implement tooling for functional, integration, performance, and resilience testing.
• Use scripting and CI/CD integrations to improve test execution, reliability, and feedback loops.
• Engineer and support AIOps capabilities using telemetry, logs, metrics, and events. Develop data pipelines and automation for anomaly detection, alert correlation, and predictive insights.
• Provide engineering-led application support with a strong focus on automation and self-healing.
• Design and improve resilience, failover, backup, and recovery capabilities.
• Participate in incident response, problem management, and post-incident reviews, driving continuous improvement.
• Develop and maintain integrations and automation for applications and security controls.
• Embed secure-by-design principles into platforms, pipelines, and operational tooling.

• Strong experience with automation and engineering languages, including: Python (automation, AIOps, data pipelines, ML workflows) JavaScript / TypeScript (platform integrations, REST APIs, tooling extensions) Bash / Shell scripting (operational automation, support tooling)
• Familiarity with AI / ML ecosystems, such as: MLflow, Kubeflow, or similar MLOps platforms PyTorch, TensorFlow, scikit-learn (model integration and operationalisation)
• Experience with REST APIs, JSON, YAML, and event-driven integrations.
• Strong experience in engineering practices in Confluence.
• Understanding of application lifecycle management, ITSM, and engineering delivery practices.
• Experience integrating tools across development, operations, and security domains.

• Agile Development
• Database Design/Development
• Debugging
• APIs/Web Service Integration
• Programming/Scripting
• Version Control
• Microservices/Service Oriented Architecture
• IT Security
• Cloud Computing
• Software Testing
• Continuous Integration/Continuous Deployment Automation & Orchestration
• Application Development
• Algorithm Design
• Software Development Lifecycle
• Decision Making
• Growth Mindset
• Inclusive Leadership