Generative AI Engineer

ppWe are bTeam possible /b – the people behind Proximus, Proximus NXT, Davinsi Labs, Codit, Proximus Ada, and more. Nice to see you here /ppUnited by a shared purpose, we’re building a smarter, trustful and more connected world. /ppThat means embracing technology and celebrating change. /ppWe think possible and then make it possible. And of course, we love what we do. /ppSounds like your kind of place? /ph3Your job /h3pAre you a passionate machine learning engineer with expertise in generative AI? Join our bMachine Learning Enablers /b team at Proximus Ada, where you’ll play a key role in advancing and scaling generative AI capabilities across teams. You will leverage your expertise in architectures such as bretrieval-augmented generation (RAG) /b and bagent-based systems /b to develop and maintain reusable components and templates that enable data scientists to deliver impactful solutions. /ppIn this role, you will collaborate closely with data scientists in delivery teams and engineers from our Cloud and DevSecOps teams to implement best practices and ensure technical excellence across multiple projects. Using frameworks such as bLangChain /b and bLangGraph /b and our bAzure-first /b stack, you will maintain and expand a shared repository of reusable generative AI assets that enable scalable, reliable solutions. /ppYour innovative mindset will help identify emerging techniques and translate them into practical building blocks that deliver business value, keeping our teams aligned with the latest advances. Your work will support the day-to-day needs of our data scientists through the practical bmaintenance /b, bhands‑on support /b, and enhancement of shared assets, while also driving innovation in our generative AI initiatives. /ph3Responsibilities /h3h3Develop and Maintain our Generative AI Repository /h3ulliManage and expand our shared repository of reusable Generative AI components and templates, ensuring it is robust, up-to-date, well-documented, and easy to adopt across use cases. /liliSupport onboarding and adoption: help teams use the repository effectively, keep alignment with the main branch, and facilitate clean integration of shared changes. /liliCollaborate with data scientists to identify new components to build, provide technical support, and promote best practices in using the repository. /liliDrive key upgrades and migrations of core libraries and templates (e.g., LangChain/LangGraph) with minimal disruption to delivery teams. /li /ulh3Enable Agent-Based and Generative AI Solutions /h3ulliGuide delivery teams on architectures such as retrieval-augmented generation (RAG) and agent-based systems, providing hands‑on technical support and troubleshooting when needed. /liliResearch and prototype emerging techniques, frameworks, and Azure services; translate validated approaches into reusable building blocks for delivery teams. /li /ulh3Collaborate and Drive Technical Excellence /h3ulliDefine and promote software engineering best practices for Generative AI solutions (testing, code quality, style, automation) and enforce them through PR reviews and shared standards. /liliCollaborate with Cloud, DevSecOps, enterprise architecture, and vendors to ensure solutions and technologies align with our stack and constraints. /liliStay current with advances in Generative AI and communicate relevant learnings and recommendations to the organization. /li /ul /p