• Design, build, and deploy end-to-end AI/ML and agent-based systems, from problem definition and model development to production deployment, monitoring, and continuous improvement to solve business problems, and automate enterprise and scientific tasks. • Focus on simulating human learning activities, improving system performance through data analysis, and developing deep learning frameworks and systems. • Collaborate with scientists to build robust data pipelines and ensure high-quality training data. • Design scalable, reliable services on major cloud platforms; strong CI/CD, observability, and operational excellence. • Translate customer requirements to business solutions using data pipelines and statical models. • Build & maintain scalable ML infrastructure, including training pipelines, feature stores, and model serving systems. • Contribute to MLOps best practices, including CI/CD for ML, model versioning, and A/B testing frameworks. • Create exploratory analysis, model design & training, validation, feature engineering, production handoff to drive business optimization. • Responsible for constructing, studying, and training algorithms that learn from complex, high-dimensional data to uncover patterns and develop practical predictive models and applications. • Document architectures, experiments, and results clearly for technical and non-technical stakeholders to support current work and any retraining for the future. • Data, model, and agent pipeline engineering (e.g., workflow orchestration, model lifecycle management, automated retraining/rollouts). • Orchestration and integration across components (agent frameworks, containers, web services/APIs, distributed systems). • Develop and integrate intuitive Copilot experiences into existing tools to provide real-time, AI-driven assistance and insights to team members.

• Own the entire marketing function: strategy, content, SEO, events, partner co-marketing, and brand • You move in sprints, ship fast, and never let perfect be the enemy of good • Content quality and brand voice: Own the editorial standard across everything that goes out — LinkedIn posts, blog content, SEO copy, case studies, newsletter. You are the last human filter before anything is published. • AI content engine: Direct and maintain agentic pipelines that produce content at scale. You set direction, write the prompts, evaluate the output, and intervene when the machine gets it wrong. • Account-based marketing support: Align the content calendar with live pipeline priorities. Brief assets for key accounts. Make sure sales has what it needs, when it needs it — not generic collateral. • SEO and inbound: Own organic growth. Blog strategy, keyword targeting, distribution playbook, conversion path optimization. • Brand and thought leadership: Evolve the Retail Spotlight podcast into a content ecosystem. Ghostwrite and direct founder voice content across two distinct voices. • Build refive's presence as the authoritative voice on in-store customer engagement in Europe. • Events and field: Project-manage event participation remotely — NRF, EuroShop, RTS London and similar. Own the full loop: logistics, pre-event content, on-site coordination with vendors and booth teams, lead capture workflows, post-event follow-up content. You run this independently; founders show up and present. • Partner co-marketing: Develop joint campaigns and launch materials with white-label and integration partners as the pipeline scales. • Metrics and reporting: Own the automated weekly marketing dashboard (GA4, HubSpot, LinkedIn). Know your numbers. Flag what is not working before anyone asks.

• Co-own the underlying infrastructure that powers our OS, ensuring it is clean, consistent and well structured (you’ll work closely with domain experts, including our data & product engineers and designers) • Curate the skills, connectors, APIs and data layers that make building safe, fast and dependable • Ensure our foundation infra is accessible as a set of building blocks that others can build on with confidence • Quickly build key internal tools that help our Revenue team (Marketing, Sales and Client Success) deliver high-value work • Work closely with our Founder and Revenue team to identify problems and opportunities that should be solved with internal tooling • Iterate on tools based on real usage and feedback, treating internal teams as your customers • Design the foundations and workflows that allow non-technical colleagues to iterate on their tools using low-code platforms • Support and guide teams as they build, helping them get the most out of the platform without becoming a bottleneck • Approach internal tools as a product, grounded in a strong understanding of discovery and Jobs to be Done • Engage directly with users to understand their needs before building, rather than working from a list of requested features • Make pragmatic design decisions: interfaces don't need to be pixel-perfect, but are highly intuitive and genuinely useful

• Build new AI-powered product features from idea to production • Improve existing AI workflows for quality, reliability, latency, and user value • Design and implement LLM-based workflows, structured outputs, validation logic, and fallback behavior • Build evaluation loops, tests, and quality checks for AI-generated outputs • Integrate AI capabilities into existing product and backend systems • Work with commercial and open-source LLMs without being tied to one specific provider • Support self-hosted model workflows where they make sense for quality, speed, cost, or control • Debug AI feature failures across inputs, outputs, data, backend logic, and user flows • Use AI development tools as a core part of your daily workflow • Ship quickly while keeping production quality high