About the role
Tanzo Technologies Ltd is seeking a DevOps & AI Test Engineer to help build reliable deployment pipelines and test software applications, including AI-enabled features. This role offers the opportunity to contribute to automation, software quality and continuous improvement.
Role description
You will work across DevOps and quality engineering, helping ensure that software is thoroughly tested, deployed consistently and monitored effectively. You will develop automated tests, maintain CI/CD pipelines and evaluate AI-enabled applications for accuracy, reliability and performance.
Working closely with developers and business stakeholders, you will investigate defects, improve test coverage and support dependable software releases.
Key responsibilities
- Build and maintain CI/CD pipelines for automated testing and deployment.
- Develop automated tests for APIs, back-end services and web applications.
- Test AI-enabled features, including evaluating response quality, consistency and handling of unexpected inputs.
- Create repeatable AI evaluation datasets and regression tests.
- Manage test environments, configuration and infrastructure automation.
- Support containerised applications and cloud deployments.
- Monitor application health, analyse logs and troubleshoot build, deployment and runtime issues.
- Document defects, test results and release readiness.
- Integrate appropriate security and performance checks into delivery workflows.
Essential qualifications
- Practical experience in DevOps, test automation or software engineering.
- Proficiency in Python or another relevant programming language, with scripting skills.
- Experience with Git and a CI/CD platform such as GitHub Actions, GitLab CI, Jenkins or Azure DevOps.
- Experience testing APIs and developing automated tests using frameworks such as pytest, Playwright, Selenium or equivalent.
- Familiarity with Linux, Docker and cloud platforms such as AWS, Azure or Google Cloud.
- Understanding of test planning, regression testing, defect investigation and software delivery practices.
- Understanding of AI testing challenges, including variable outputs, factual accuracy and evaluation criteria.
- Strong problem-solving, communication and collaboration skills.
Desirable experience
- Infrastructure as code using Terraform or similar tools.
- Kubernetes and application monitoring tools.
- Testing large language model applications, retrieval-augmented generation (RAG) or AI agents.
- AI security testing, including prompt injection and sensitive-data exposure.
- Performance and load testing.
- A degree in Computer Science, Software Engineering or a related subject, or equivalent practical experience.