• Du bist Teil unseres AI Boards und baust gemeinsam mit dem Team die AI Infrastruktur auf, die unsere AI-first Transformation ermöglicht: Governance & Standards: Du baust eigene Automatisierungen – und leitest daraus Standards ab, die für das gesamte Unternehmen gelten. • AI-Workflows Coaching: Mitarbeitende aus Marketing, HR, Sales und anderen Bereichen bauen ihre eigenen Automatisierungen. Du begleitest sie: Einsatzzweck definieren, strukturiert einführen, gemeinsam prüfen, ob es funktioniert. • AI Board Operations: Du hältst die Werkzeuge aktuell, die das AI Board am Laufen halten: Zugriffshandbuch, Agenten-Register, monatlicher Statusbericht für die Unternehmensleitung. • Hands-on Automation: Du baust aktiv eigene Automatisierungen und übernimmst Verantwortung für ausgewählte Agenten – damit deine Beratung auf echter Erfahrung basiert, nicht nur auf Theorie.

• Lead the architecture and hands-on implementation of end-to-end ML systems • Own technical decisions across the full stack • Set engineering standards for ML projects • Coach and uplift other engineers on the team • Partner with the sales leadership team across pre-sales activity • Lead architecture and solutioning conversations with prospects and customers • Provide dedicated technical support to opportunities flowing through the partners sales process • Contribute to thought leadership and demand generation

• Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution. • Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures). • Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach. • Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. • Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. • Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning. • Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution. • Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs.

• Act as the primary point of contact for clients and partners during AI implementation initiatives, ensuring clear communication, expectation alignment, and structured execution. • Guide clients in translating business requirements into AI deployment strategies leveraging QVAC capabilities (local inference, delegated compute, privacy-preserving architectures). • Support Expansion team in shaping AI-related opportunities by providing input on feasibility, integration complexity, and delivery approach. • Identify opportunities to extend implementations across additional use cases, geographies, or Tether technologies. • Lead end-to-end coordination of QVAC-based implementations from kickoff through production deployment. • Define implementation roadmaps, milestones, and dependencies across AI models, infrastructure, and integration layers. • Ensure alignment between client expectations and actual product capabilities, avoiding scope drift or mispositioning. • Track progress across multiple concurrent AI deployments, ensuring timely delivery and readiness for production environments. • Coordinate closely with product, engineering, and research teams to align on QVAC capabilities, limitations, and roadmap evolution. • Facilitate integration between client systems and QVAC components, including model deployment pipelines, APIs, and compute environments. • Work with legal and compliance teams where required, particularly in sensitive AI deployments involving data locality or privacy constraints. • Maintain structured communication flows across all stakeholders involved in the implementation lifecycle. • Establish and maintain governance frameworks including implementation plans, risk tracking, and decision logs. • Produce executive-level updates summarizing progress, risks, blockers, and next steps. • Ensure documentation of implementation architectures, deployment patterns, and key learnings for reuse across future projects. • Support escalation management and ensure timely resolution of technical or operational challenges.