Lead AI Software Engineer
Who we are
About this Role
Location: Newbury or Paddington (hybrid)
What you will do
- Lead build execution within a squad, platform capability, or engineering domain.
- Translate specifications, designs, and architectural intent into clear implementation plans and verifiable engineering tasks.
- Decompose solution designs into small, sequenced, testable delivery increments.
- Guide engineers and AI coding agents through implementation, validation, and release activities.
- Deliver and oversee complex, high-risk, or business-critical software components.
- Review AI-generated and engineer-written code to ensure correctness, maintainability, security, and alignment with specifications.
- Drive engineering excellence through automated testing, contract testing, regression testing, observability, and production verification.
- Support CI/CD processes, deployment readiness, operational handover, runbooks, and service ownership.
- Ensure AI-generated outputs are explainable, traceable, secure, and compliant with engineering standards.
- Escalate architectural ambiguity, cross-domain risks, and decisions beyond agreed engineering guardrails.
- Identify recurring engineering or AI-agent delivery issues and transform them into improved controls, guidance, and quality practices.
- Coach engineers on AI-native software engineering, implementation planning, code review, testing practices, and responsible AI usage.
- Contribute to the evolution of AI-native Software Development Life Cycle practices, developer experience, automation, and engineering productivity.
Who you are
- Significant experience delivering production-grade software within complex engineering environments.
- Strong hands-on expertise in Java and Spring Boot, with experience in React or Angular.
- Proven experience designing and implementing RESTful APIs, microservices, integrations, platform services, and digital applications.
- Strong understanding of cloud-native architectures, distributed systems, containerised environments, and modern integration patterns.
- Experience building event-driven solutions using technologies such as Kafka, RabbitMQ, or equivalent platforms.
- Demonstrated ability to lead software implementation within agile engineering teams or technical domains.
- Experience with CI/CD, continuous delivery practices, automated testing frameworks, observability, and production support.
- Ability to convert specifications, acceptance criteria, and architectural designs into actionable implementation plans and verified software.
- Strong code review and diff-review capability, including validation of AI-generated software outputs.
- Experience using AI-assisted engineering tools and effectively steering AI coding agents.
- Understanding of responsible AI practices, including validation, security, traceability, governance, and quality assurance.
- Excellent stakeholder engagement, coaching, collaboration, and communication skills.
- Strong focus on software quality, resilience, operational readiness, and continuous improvement.
What’s in it for you
- Opportunity to shape and deliver next-generation digital and technology capabilities that support Vodafone’s future growth.
- Exposure to AI-native engineering practices and modern software delivery methodologies.
- Opportunity to work on cloud-native platforms, reusable services, APIs, integrations, and large-scale digital products.
- Collaboration with highly skilled engineers, architects, platform specialists, and product teams across global markets.
- Involvement in modern engineering disciplines including automation, continuous delivery, observability, and platform engineering.
- Ability to influence engineering standards, software quality, delivery practices, and operational excellence.
What skills you will learn
- Advanced AI-native engineering and AI-agent orchestration techniques.
- Large-scale cloud-native software architecture and distributed systems practices.
- Modern software delivery frameworks, automation strategies, and developer productivity improvements.
- Advanced observability, operational readiness, and production engineering capabilities.
- Enterprise-scale implementation planning, architecture alignment, and engineering governance.
- Coaching, mentoring, and technical leadership skills within multi-disciplinary engineering environments.
VOIS Equal Opportunity Employer Commitment
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