pThis 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. /p h3Responsibilities /h3 ul liDefine and establish a production-grade AI-assisted engineering practice, starting with areas such as automated code review, testing, and living documentation. /li liAssess 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. /li liUse strong engineering expertise to shape solutions, evaluate tools and approaches, guide implementation, and ensure practices meet production-quality standards. /li liShape how the practice extends across the software delivery lifecycle, including specification, design and architecture, AI-paired coding, CI/CD, and release orchestration. /li liEnable adoption across engineering teams through clear standards, appropriate tooling, workshops, pairing, and knowledge transfer, building trust with experienced engineers and stakeholders. /li liEnsure AI-assisted engineering practices operate effectively within enterprise constraints, including legacy environments, approved tooling, network controls, audit requirements, and governance over code and data. /li /ul h3Experience /h3 ul liExtensive software engineering experience, including senior, lead, or technical leadership responsibility. /li liProven experience applying AI-assisted development in real engineering workflows and translating experimentation into practical, production-grade approaches. /li liDemonstrated experience introducing or developing new engineering practices, tools, or ways of working and bringing others along in their adoption. /li liDemonstrated ability to lead technical change, influence experienced engineering teams, and drive adoption of new practices. /li liStrong track record of communicating complex technical topics clearly and effectively across technical and non-technical stakeholders. /li liGenuine curiosity for AI and emerging engineering practices, with evidence of actively exploring how new technologies can improve software delivery. /li /ul h3Technical fluency /h3 ul liStrong Java experience and technical fluency, with the depth required to work credibly with experienced engineering teams. /li liPython for tooling, automation, and AI-assisted engineering workflows. /li liSolid command of software delivery disciplines: code quality, testing strategy, CI/CD, architecture, release, and delivery governance. /li liStrong understanding of AI-assisted development tools, agents, prompting, and engineering workflows. /li liExperience with orchestrated development frameworks such as GStack or equivalent is a plus, but not essential. /li liComfortable building a production-grade practice within regulated enterprise environments, including approved tooling, network controls, and audit expectations. /li /ul h3Ways of working /h3 ul liCommunicate complex technical concepts clearly, concisely, and in a structured way to both technical and non-technical audiences. /li liBuild trust and influence across engineering teams and stakeholders, creating momentum around new ways of working. /li liBring genuine curiosity and enthusiasm for AI, with the ability to engage others and encourage adoption. /li liDemonstrate leadership and ownership, particularly when navigating challenging, ambiguous, or changing situations. /li liAble to articulate and defend technical recommendations, explain trade-offs, and adapt the message to the audience. /li liStructured and pragmatic, with the confidence to challenge existing approaches constructively and define a practical path forward. /li /ul h3Qualifications /h3 ul liTrack record of designing, introducing, or scaling AI-assisted engineering practices; experience in regulated environments (finance, insurance, health, energy, or public sector) is a plus. /li liFluent French and written technical English. /li liEligibility to work in Switzerland. /li /ul pBy 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. /p #J-18808-Ljbffr
AI Engineering and Adoption Lead in Lausanne Arbeitgeber: TSG Corp
TSG Corp in Genf bietet eine dynamische und unterstützende Arbeitsumgebung, die auf Innovation und Teamarbeit setzt. Als Avaloq Developer profitieren Sie von umfangreichen Weiterbildungsmöglichkeiten und einer Kultur, die persönliches Wachstum fördert. Zudem genießen Sie die Vorteile eines internationalen Unternehmensstandorts, der Ihnen Zugang zu einem vielfältigen Netzwerk und spannenden Projekten im Bereich Core Banking und Wealth Management bietet.
