This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As an AI Fullstack Architect, you will spearhead the design and delivery of cutting-edge AI-driven solutions that span the entire technology stack—from intuitive frontend interfaces to robust backend services, sophisticated AI layers, and seamless deployment pipelines. Your expertise will be pivotal in shaping scalable, secure, and high-performance systems that integrate the latest advances in generative AI, machine learning, and computer vision, driving innovation and operational excellence across our AI initiatives. In this role, you will: - Architect and implement high-performance backend APIs using Python and FastAPI. - Craft responsive, modern frontend applications with React and Next.js. - Integrate generative AI capabilities such as large language models (LLMs), retrieval-augmented generation (RAG), prompt engineering, and fine-tuning, alongside traditional ML models and OpenCV-based computer vision solutions. - Drive rapid prototyping cycles to validate concepts swiftly. - Enforce best practices in software architecture and MLOps. - Implement comprehensive automated testing strategies to ensure robust, maintainable codebases. Day-to-day, you will: - Collaborate closely with cross-functional teams—including data scientists, domain experts, product owners, and DevOps engineers—to deliver production-ready AI systems that meet stringent industrial standards for compliance, auditability, and reliability. - Lead Agile Scrum ceremonies, manage backlogs and sprints via Azure DevOps, and mentor engineers through architecture reviews and knowledge sharing, fostering a culture of technical excellence and continuous improvement. Joining our dynamic, innovation-driven environment, you will have the opportunity to influence the future of AI applications at scale, grow your leadership capabilities, and work alongside passionate experts committed to pushing the boundaries of technology. Our collaborative team structure emphasizes transparency, agility, and shared ownership, empowering you to make a tangible impact on transformative AI solutions that redefine industry standards. Qualifications - Experience in architecting end-to-end AI-fullstack solutions. - Proficiency in Python and FastAPI for backend development. - Strong skills in React and Next.js for frontend development. - Knowledge of generative AI capabilities and traditional ML models. - Experience with automated testing strategies using pytest. - Familiarity with Agile Scrum methodologies and Azure DevOps. Requirements - Ability to mentor engineers and conduct architecture reviews. - Champion technical excellence across the team. - Ensure solutions meet stringent industrial requirements (compliance, auditability, reliability, low latency where required). Benefits - Opportunity to influence the future of AI applications at scale. - Growth in leadership capabilities. - Collaborative team structure emphasizing transparency and agility.

• Own end-to-end delivery of features (design → deployment → support) • Build scalable, maintainable systems for evolving product needs • Partner with product to clarify requirements and deliver practical solutions • Improve reliability and code quality through strong engineering practices • Participate in on-call rotation and contribute to operational excellence

• empower our 25+ person marketing team to manage content autonomously through our CMS and emerging AI tools • build memorable digital experiences including campaign microsites like our L&D Maturity Model that bring our brand and product story to life • support our acquisition channels (paid, content, partners, SEO/GEO) with high-performance, conversion-optimized pages • integrate deeply with our martech stack (Marketo, Wistia, Chili Piper, AI SEO tooling) to keep our growth engine humming • continuously experiment with new libraries and automation that make our site faster, smarter, and more creative • shape every stage of development—from concept to deployment • work on an attractive stack (Vuejs, TS, Nuxt, Prismic) • grow within a R&D team that allows rapid progress: Our decentralized peer review process provides us with qualitative and regular feedback from other team members. We promote pair programming and knowledge sharing.

• Develop the internal testing framework (written in Java and partly open source). • Create new test utilities and internal services. • Automate routine tasks to simplify life for yourself and your colleagues.