Software Engineer, Quality & Platform (GenAI)

Role Overview

We are seeking a Software Engineer, Quality & Platform (Generative AI) to support the quality, reliability, security, and performance of enterprise-grade AI applications and agent orchestration platforms.

This role combines software engineering, test automation, platform quality assurance, and Generative AI validation. The successful candidate will contribute to the establishment of testing frameworks, quality engineering practices, AI evaluation methodologies, and platform engineering capabilities. Over time, the role will expand into software development, platform enhancement, and data engineering initiatives.

Key Responsibilities

Quality Engineering and Test Automation

. Design, develop, and maintain automated testing frameworks for enterprise AI applications and platform services.

. Develop test strategies, test plans, and quality assurance processes covering application functionality, APIs, integrations, security, and user interfaces.

. Establish automated validation approaches for AI-generated outputs, Retrieval-Augmented Generation (RAG) solutions, and AI workflows.

. Design and maintain high-quality test datasets, synthetic test data, and evaluation scenarios while ensuring compliance with data privacy and security requirements.

. Evaluate AI application behaviour, model responses, prompt changes, and platform quality metrics.

API and Streaming Validation

. Design and execute automated tests for APIs, streaming services, and real-time application components.

. Validate application workflows, state transitions, error handling, timeout management, and integration reliability.

. Support testing of backend services and distributed system interactions.

Security and Platform Testing

. Validate role-based access controls, tenant isolation mechanisms, authentication workflows, and platform security controls.

. Perform testing of isolated execution environments, application sandboxing, and secure workflow execution.

. Support security validation activities and contribute to platform risk mitigation initiatives.

End-to-End Automation

. Design, develop, and maintain end-to-end automation frameworks using modern testing technologies.

. Validate user interface components, workflow interactions, document processing features, and application integrations.

. Ensure application quality across multiple environments and deployment stages.

CI/CD and Quality Governance

. Integrate automated testing frameworks within CI/CD pipelines.

. Establish quality controls and deployment validation processes to support reliable software delivery.

. Collaborate with engineering and DevSecOps teams to improve platform quality and deployment readiness.

Performance and Reliability Testing

. Develop and execute performance, load, scalability, and reliability testing activities.

. Monitor application performance characteristics and identify potential bottlenecks.

. Support optimisation efforts for AI services, APIs, and platform infrastructure.

Cross-Functional Engineering Responsibilities

. Contribute to software development activities, platform enhancements, and feature implementation as platform quality frameworks mature.

. Support data engineering, analytics, and platform initiatives where required.

. Promote quality engineering best practices and support development teams in implementing automated testing and validation approaches.

Requirements

Qualifications and Experience

. Bachelor's Degree in Computer Science, Software Engineering, Information Technology, or a related discipline.

. At least 3 years of experience in Software Engineering, Quality Engineering, Test Automation, or Software Development Engineer in Test (SDET) roles.

. Strong programming skills in Python and JavaScript/TypeScript.

. Experience developing automated testing frameworks using tools such as Playwright, Cypress, Pytest, Postman, or equivalent technologies.

. Experience testing APIs, distributed systems, and cloud-native applications.

. Strong troubleshooting, debugging, and root-cause analysis capabilities.

. Experience working with containerised or distributed environments.

. Proficiency in SQL and relational database technologies, including PostgreSQL.

. Familiarity with cloud platforms and services, including AWS or equivalent cloud technologies.

. Experience handling test data management, synthetic data generation, and privacy-sensitive environments.

. Interest in Generative AI technologies, AI application testing, Retrieval-Augmented Generation (RAG), and AI platform quality assurance.

Preferred Experience

. Previous experience in software development, data engineering, analytics, or platform engineering.

. Experience with automated security testing tools and application security validation.

. Experience working in highly regulated, security-sensitive, or compliance-driven environments.

. Familiarity with AI evaluation, observability, monitoring, or model validation frameworks.

Additional Information

. Appointment level and remuneration will be commensurate with qualifications, skills, and relevant experience.