Working at the forefront of energy innovation, building scalable cloud-native solutions that power our digital transformation and helping millions of customers manage their energy more effectively.
If you want to work on complex, high‑impact problems using modern engineering practices, and help build reusable platforms that will shape how Centrica operates over the next decade, this is the place to do it.
Day‑to‑Day Responsibilities
- Champion solid engineering fundamentals including effective use of source control, CI/CD pipelines, and modern engineering practices
- Utilise Azure DevOps and GitHub for work management, repositories, pipelines, and artifacts
- Implement comprehensive observability solutions using Datadog for monitoring and performance optimisation
- Ensure security and code quality through automated scanning and testing processes
- Leverage Launch Darkly for feature flag management and controlled rollouts
Problem Solving & Decision Making
- Design and develop full-stack applications using Node.js, TypeScript, and React, ensuring high-quality, maintainable code
- Build and maintain cloud-native solutions across a comprehensive range of AWS services including Lambda, API Gateway, S3, SQS, SNS, EventBridge, Step Functions, and AWS Lex
- Implement Infrastructure as Code using Terraform to ensure consistent, scalable deployments
- Develop mobile applications using React Native with Expo for software management (where applicable)
Qualifications
- Strong proficiency in full-stack development with Node.js, TypeScript, and React
- Extensive hands‑on experience with AWS services including Lambda, API Gateway, IAM, S3, SQS, SNS, EventBridge, and Step Functions
- Solid experience with Infrastructure as Code using Terraform
- Proficiency with Azure DevOps and GitHub for development workflows
- Experience with observability tools, particularly Datadog
- Knowledge of security scanning and code quality tools
- Familiarity with feature flag management tools like Launch Darkly
Core Competencies & Technical Skills (AI & Emerging Technology)
- Designs, integrates and operates AI‑enabled solutions within enterprise environments, including prompt‑driven workflows, retrieval‑augmented systems and AI agents
- Applies structured evaluation, testing and monitoring practices to ensure AI outputs are reliable, secure and compliant with organisational guardrails
- Prepares and manages data used in AI workflows and takes responsibility for the responsible lifecycle of AI features from experimentation through deployment and continuous improvement
Key Stakeholders
- Software Engineering Managers
- Principal Software Engineers
- Product teams
- Security teams
- Infrastructure teams
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