• Define integration scope, success criteria, and deployment strategy during late-stage sales cycles • Lead implementation efforts across CMS, DAM, and workflow automation tools in client environments • Design and validate agent-powered workflows that streamline content creation, personalization, and publishing • Act as the voice of the customer with Product and Engineering, translating implementation challenges into roadmap opportunities • Drive go-live, QA, and UAT processes with clear ownership of time-to-value • Deliver enablement resources, training, and documentation to support long-term adoption • Build trusted relationships with client-side marketing and technical stakeholders

• Own and execute retention and growth strategy across the user lifecycle • Identify friction points and optimize onboarding and activation flows • Improve time-to-value and early user engagement • Conduct customer research and product discovery (interviews, churn analysis, experimentation) • Build and leverage product analytics dashboards and tracking frameworks • Translate data insights into product improvements and growth initiatives

• AI product development: advance LLM/RAG and multi-agent flows (orchestration, tooling, guardrails, evaluation) • Compliance & security: ensure GDPR/EU AI Act compliance, apply privacy-by-design, and establish safety policies and evaluation • Product strategy & roadmap: refine product vision, define objectives, set priorities, and maintain the backlog • Discovery & UX: research, hypothesis generation, prototyping, A/B experiments, and validation • Langfuse ownership: set up datasets, scoring and evaluation workflows; build dashboards and alerting for quality, safety, and performance • Delivery: drive incremental improvements • Data & quality: enrich knowledge/vector stores, implement monitoring and feedback loops, reduce hallucinations and bias • Measurability: define metrics (e.g., task success, latency, safety triggers) and operationalize them in dashboards and experiment analyses

• Own product growth and performance for Kits AI across funnel optimization, activation, retention, pricing, and monetization. • Drive Kits product strategy: identify high-impact opportunities and launch product and growth initiatives that move the business. • Productize new ML capabilities into valuable creator-facing products and workflows, partnering closely with research and engineering. • Develop a deep customer understanding through user interviews, analytics, and automated customer insight pipelines. • Track product performance in our data-analysis platform, own experimentation, and use data to make sharp prioritization calls. • Leverage the latest AI tools to dramatically accelerate your workflow, from shipping features directly to production with AI coding tools to building custom internal systems for customer insight, research, and product discovery.