Junior AI Software Engineer
Summary
Junior AI Software Engineer builds and validates AI-assisted software specs, code, and tests in cross-functional squads using Java/Python/JavaScript and cloud-native tools.
Who we are
About this Role
- Support the analysis of existing systems to identify business logic, integration patterns and reusable capabilities.
- Use AI tools to support analysis of codebases and services, helping identify reusable logic and engineering patterns.
- Generate and refine specifications, acceptance criteria and user stories aligned with platform architecture.
- Create test scenarios and validation artefacts derived from specifications.
- Support the translation of business requirements into implementation-ready engineering artefacts.
- Collaborate with developers to ensure alignment between specifications, code and testing outputs.
- Validate AI-generated specifications, code suggestions, test scenarios and documentation to ensure accuracy, consistency, security and alignment with engineering standards.
- Support responsible AI-SDLC practices by identifying risks such as incomplete logic, security gaps and misalignment between business requirements and implementation.
- Contribute to incremental, thin-slice delivery while maintaining traceability between requirements, specifications and implementation.
- Assist with the implementation of services, APIs and platform components.
- Participate in agile ceremonies including refinement, planning, daily stand-ups and retrospectives.
- Contribute to AI-SDLC practices, templates and continuous improvement across D&IT squads.
- Experience with at least one programming language such as Java, Python, JavaScript or similar.
- Understanding of APIs, web services and basic system integration concepts.
- Familiarity with modern development workflows including Git and CI/CD fundamentals.
- Awareness of AI and Large Language Model (LLM) tools and their application within software development.
- Exposure to cloud-native development concepts such as microservices, containers or cloud platforms.
- Degree in Computer Science, Engineering, Data Science or equivalent experience.
- Understanding of how AI tools can support software engineering, specification development and delivery workflows.
- Awareness of responsible AI practices, including validation, traceability, quality assurance and security considerations.
- Strong communication and documentation skills.
- Ability to collaborate effectively within cross-functional teams.
- Curiosity, adaptability and enthusiasm for continuous learning.
- Exposure to agile delivery and continuous improvement practices.
Not a Perfect Fit?
- Opportunity to work with AI-enabled software engineering practices in a fast-evolving technology environment.
- Exposure to specification-led and AI-assisted software delivery methodologies.
- Experience working alongside software engineers, architects and product teams.
- Development opportunities across AI, cloud-native technologies and modern engineering practices.
- Participation in innovative digital transformation programmes within D&IT.
- AI-assisted software engineering and AI-SDLC methodologies.
- System analysis and requirements decomposition techniques.
- Specification writing, user story creation and validation processes.
- API and service-based architecture design principles.
- Traceability between requirements, implementation and testing.
- Agile delivery and continuous improvement practices.
- Responsible AI usage within software development environments.