Lead AI Software Engineer

Who we areVOIS (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.#VOIS #Be Unrivalled #Create The Future About  this Role

Location:

Newbury or Paddington (hybrid)
We are seeking a Lead AI Software Engineer to lead software implementation and engineering delivery across squads, platform capabilities, or engineering domains. This is a senior hands-on role responsible for translating specifications, solution designs, and architectural direction into scalable, secure, production-ready software.

You will combine deep software engineering expertise with strong judgement in the use of AI-native engineering practices, ensuring AI-generated code, tests, documentation, and engineering artefacts are accurate, maintainable, secure, and aligned to business requirements. Working closely with Technical Leads, Architects, Product Owners, Platform Engineers, and delivery teams, you will drive implementation quality, testing, observability, operational readiness, and continuous improvement throughout the software development lifecycle.

What you will doLead 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…