Beschreibung

AI Engineering & Adoption Lead | Senior technical leadership | Switzerland (Suisse romande) | Regulated Financial Services & Insurance | Java, Python & production-grade AI-assisted engineering; build, establish and scale the engineering practices that move AI-assisted development from experimentation to trusted, organisation-wide adoption. About the role: This role is for an experienced engineering leader who can turn AI-assisted development into a trusted, production-grade practice across engineering teams. It combines strong technical credibility with the leadership, communication, and influence required to introduce new ways of working. The goal is to define what good AI-assisted engineering looks like, prove it in practice, and create the conditions for teams to adopt and scale it. Responsibilities • Define and establish a production-grade AI-assisted engineering practice, starting with areas such as automated code review, testing, and living documentation. • Assess existing development practices and identify where AI-assisted approaches can create meaningful value, defining what to introduce, how to validate it, and how it can scale. • Use strong engineering expertise to shape solutions, evaluate tools and approaches, guide implementation, and ensure practices meet production-quality standards. • Shape how the practice extends across the software delivery lifecycle, including specification, design and architecture, AI-paired coding, CI/CD, and release orchestration. • Enable adoption across engineering teams through clear standards, appropriate tooling, workshops, pairing, and knowledge transfer, building trust with experienced engineers and stakeholders. • Ensure AI-assisted engineering practices operate effectively within enterprise constraints, including legacy environments, approved tooling, network controls, audit requirements, and governance over code and data. Experience • Extensive software engineering experience, including senior, lead, or technical leadership responsibility. • Proven experience applying AI-assisted development in real engineering workflows and translating experimentation into practical, production-grade approaches. • Demonstrated experience introducing or developing new engineering practices, tools, or ways of working and bringing others along in their adoption. • Demonstrated ability to lead technical change, influence experienced engineering teams, and drive adoption of new practices. • Strong track record of communicating complex technical topics clearly and effectively across technical and non-technical stakeholders. • Genuine curiosity for AI and emerging engineering practices, with evidence of actively exploring how new technologies can improve software delivery. Technical fluency • Strong Java experience and technical fluency, with the depth required to work credibly with experienced engineering teams. • Python for tooling, automation, and AI-assisted engineering workflows. • Solid command of software delivery disciplines: code quality, testing strategy, CI/CD, architecture, release, and delivery governance. • Strong understanding of AI-assisted development tools, agents, prompting, and engineering workflows. • Experience with orchestrated development frameworks such as GStack or equivalent is a plus, but not essential. • Comfortable building a production-grade practice within regulated enterprise environments, including approved tooling, network controls, and audit expectations. Ways of working • Communicate complex technical concepts clearly, concisely, and in a structured way to both technical and non-technical audiences. • Build trust and influence across engineering teams and stakeholders, creating momentum around new ways of working. • Bring genuine curiosity and enthusiasm for AI, with the ability to engage others and encourage adoption. • Demonstrate leadership and ownership, particularly when navigating challenging, ambiguous, or changing situations. • Able to articulate and defend technical recommendations, explain trade-offs, and adapt the message to the audience. • Structured and pragmatic, with the confidence to challenge existing approaches constructively and define a practical path forward. Qualifications • Track record of designing, introducing, or scaling AI-assisted engineering practices; experience in regulated environments (finance, insurance, health, energy, or public sector) is a plus. • Fluent French and written technical English. • Eligibility to work in Switzerland. Your data: By submitting your resume, you agree to the retention and use of your personal data for recruitment purposes, including sharing with our clients in the context of your application. The identity and sector of the client will be disclosed to shortlisted candidates ahead of interview.