• Design and build AI-powered workflows for marketing execution • Create agent-based systems for: Content production, Email marketing, Reporting, Customer insights • Connect tools and systems (Claude, APIs, automation platforms) • Ensure workflows are scalable, reusable, and efficient • Conduct keyword research and clustering (high-intent focus) • Build AI-assisted content pipelines (blogs, landing pages) • Optimize existing content and improve rankings • Implement internal linking, metadata, and schema strategies • Perform competitor content analysis • Manage Google Business Profile updates and posts • Draft and optimize review responses and FAQs • Handle citation building and NAP consistency • Support location-based keyword targeting • Build and optimize campaigns and flows (Klaviyo or similar) • Manage lifecycle flows (welcome, abandoned cart, post-purchase, winback) • Support segmentation and subject line testing • Track revenue attribution and performance • Monitor workflows and ensure systems run reliably • Troubleshoot errors and optimize performance • Continuously improve automation based on results • Prepare weekly marketing performance summaries • Analyze channel performance and funnel metrics (traffic → conversion → retention) • Identify drop-offs and growth opportunities • Work closely with stakeholders to translate ideas into working systems • Participate in daily syncs (initially) and async communication

• Provides independent advisory, oversight, and validation of governance, risk, and control activities that support Enterprise Data Governance and AI Governance • Supports Product/Service/Process Risk Assessments (PSPRA) and Regulatory Compliance Risk Assessment (RCRA) • Maintains Process Risk and Control (PRC) libraries and advises on Key Risk Indicators (KRIs) • Works in close collaboration with First Line of Defense (1LOD) and Regulatory Compliance and Risk related Second Line of Defense (2LOD) partners • Maintains a strong understanding of applicable regulatory requirements, industry standards, and internal policy frameworks • Monitors changes and provides timely governance, risk, and control insights • Communicates governance, risk, and control considerations clearly to stakeholders, supporting informed decision-making and consistent application of expectations

Role Description Wir suchen einen Visionär, der digitale Produkte im Coaching-Umfeld baut, die sich menschlich anfühlen. - Die Mission: Wir entwickeln digitale Begleiter für persönliches Wachstum. Coaching ist emotional – unsere Tech muss das widerspiegeln. Wir brauchen keine statischen Apps, sondern fluide, reaktive Interfaces, die Nutzer genau dort abholen, wo sie stehen. - Deine Rolle: Vibe & Velocity: Du bist der Architekt und die ausführende Kraft. Du nutzt moderne LLMs und AI-Coding-Tools, um Ideen in Rekordzeit in funktionierende Prototypen und skalierbare Produkte zu verwandeln. - Rapid Prototyping: Du bringst Ideen innerhalb von Stunden (nicht Wochen) live ("Idea to URL"). - Vibe First: Du hast ein Auge für UI/UX. Du verstehst, dass Animationen, Micro-Interactions und Copywriting den Unterschied zwischen einer "App" und einer "Erfahrung" machen. - AI-Native Workflow: Du "codest" mit natürlicher Sprache. Du weißt, wie man Cursor, Claude oder GPT-4 nutzt, um komplexe Logik zu bauen, und korrigierst/optimierst den Output. - Full-Stack Mindset: Ob Datenbank-Anbindung oder Frontend-Sparkles – du kümmerst dich darum, dass es läuft. Qualifications - Mindset: Du nennst dich vielleicht "Product Engineer", "Creative Technologist" oder einfach "Maker". Du liebst es zu shippen. - Tech-Verständnis: Du beherrschst JavaScript/TypeScript (React, Next.js, Tailwind) oder Python – aber vor allem beherrschst du die Kunst, prompts zu schreiben, die guten Code erzeugen. - Coaching-Affinität: Du interessierst dich für Themen wie Persönlichkeitsentwicklung, Psychologie oder Mentoring. Du willst Produkte bauen, die Menschen wirklich helfen. - Autonomie: Du brauchst kein Händchenhalten. Du brauchst eine Vision und die Freiheit, sie umzusetzen. Benefits - Erfolgsbeteiligung (Revenue Share / Profit Share): Wenn das Produkt fliegt, fliegst du mit. Du partizipierst direkt am finanziellen Erfolg der Produkte, die du baust. (Hier gibt es kein Deckel nach oben). - 100% Remote & Flexibel: Arbeite von Bali, Berlin oder Buxtehude. Solange der Vibe stimmt und die Produkte live gehen, ist dein Standort egal. - Impact: Du baust keine langweilige B2B-Verwaltungssoftware, sondern Tools, die Leben verändern.

• Lead the development and maintenance of the enterprise data domain model, taxonomy, and ontologies to ensure shared understanding, semantic consistency, and discoverability of data and knowledge assets. • Design and evolve information and semantic models that make enterprise data AI‑ready, supporting use cases ranging from traditional analytics and BI to applied machine learning and LLM‑based experiences (e.g., search, retrieval‑augmented generation, and copilots). • Operationalize data models, taxonomies, and semantic structures through the Enterprise Data Catalog (Alation). • Define and enforce standards for data modeling, taxonomy, nomenclature, and semantic structures to ensure consistency and interoperability across business domains and downstream consumption patterns. • Provide authoritative guidance on semantic conflicts—resolve definition discrepancies, harmonize terms, and mediate cross‑domain dependencies to establish trusted, reusable business meaning. • Contribute to the enterprise data product framework by defining domain boundaries, shared dimensions, and semantic contracts that enable cross‑domain interoperability and AI consumption. • Confirm and document prioritized metadata elements for key business processes, analytical use cases, and AI‑enabled workflows, ensuring alignment with governance standards and risk expectations. • Identify simplification opportunities—reduce redundancy, converge overlapping datasets, and promote canonical sources to improve trust, efficiency, and reusability across analytics and AI platforms. • Partner with analytics, data science, and AI engineering teams to ensure information architecture, metadata, and semantic context are sufficient to support explainable, governed, and trustworthy AI outcomes. • Serve as a thought partner, provide insights from modeling, catalog adoption, and AI enablement to shape governance strategy and roadmaps.