Junior AI Software Engineer

Who we are

VOIS (Vodafone Intelligent Solutions) is a strategic arm of Vodafone Group Plc, creating value for customers by delivering intelligent solutions through Talent, Technology & Transformation. As the largest shared services organisation in the global telco industry with 30,000 FTE, our portfolio of next‑generation solutions and services are designed in partnership with customers across Vodafone Group, local markets, and partner markets to simplify and drive growth.

With our strategic partner Accenture, we work alongside our Vodafone customers, other Telco and tech companies to drive transformation, meet the challenges of our industry and ensure we stay relevant and resilient. This partnership is a unique, industry‑first model which brings together the best of in‑house and 3rd party capability.

We work with customers across 28 countries from 10 VOIS locations:
Albania, Egypt, Hungary, India, Romania, Spain, Turkey, UK, Germany, Ireland, and with a network of teams in Czech Republic, Italy, Greece, and Portugal.

The Digital & IT Team is responsible for designing, building, and operating the core digital and IT capabilities that power Vodafone’s next‑generation Digital & IT platform.

As a Junior AI Engineer, you will work within cross‑functional squads to build platform capabilities using an AI‑enabled Software Development Life Cycle (AI‑SDLC). You will apply AI tools to accelerate how we understand existing systems, generate specifications, and deliver software, working alongside engineers, architects, and product teams. You will help transform existing platform assets and business requirements into structured, reusable engineering artefacts, supporting delivery through spec‑driven, thin‑slice development.

You will also support the responsible use of AI‑generated outputs by validating accuracy, completeness, security, and alignment with Vodafone engineering standards.

• Supporting analysis of existing systems to extract business logic, integrations, and reusable capabilities
• Generating structured engineering artefacts to support consistent delivery
• Contributing to AI‑assisted development workflows, ensuring alignment between requirements, specifications, and implementation
• Supporting incremental, thin‑slice delivery of platform capabilities
• Working closely with developers, architects, and product teams to maintain quality, consistency, and delivery pace

• Use AI tools to support analysis of existing codebases and services, identifying reusable logic and integration patterns
• Generate and refine specifications, acceptance criteria, and user stories aligned to platform architecture
• Create test scenarios and validation artefacts derived from specifications
• Support translation of business requirements into implementation‑ready engineering artefacts
• Work with developers to ensure alignment between specifications, code, and testing outputs
• Validate AI‑generated specifications, code suggestions, test scenarios, and documentation to ensure they are accurate, secure, consistent, and aligned with platform architecture and engineering standards
• Support responsible AI‑SDLC practices by identifying risks such as hallucinated requirements, incomplete logic, security gaps, or misalignment between business intent and implementation
• Contribute to incremental, thin‑slice delivery, maintaining traceability between requirements, specifications, and implementation
• Assist in the implementation of services, APIs, and platform components, validating AI‑generated outputs
• Participate in agile ceremonies (refinement, planning, stand‑ups, retrospectives)
• Contribute to AI‑SDLC practices, templates, and continuous improvement across the squad
• AI‑Assisted Engineering– understanding how AI tools support system analysis, specification, and delivery workflows
• Software Engineering Fundamentals– knowledge of APIs, data structures, and system design basics
• AI Governance and Validation– awareness of responsible AI usage in software delivery, including validation of AI‑generated outputs, traceability, quality control, and security considerations
• Collaboration–…