Jobs at Zeno

Lead system-level product design for a legal AI platform: define coherent workflows, design the intelligence interaction model, set quality and accessibility standards, prototype interactions, and ship closely with engineering to create reliable, traceable experiences for legal professionals.

Own and scale the revenue infrastructure: integrate and maintain CRM and enrichment tools, build reliable data pipelines and ICP scoring, automate lead routing and outreach, create funnel dashboards, enforce data quality, and integrate AI to reduce manual work and improve GTM decision-making.

Own AI-driven product capabilities end-to-end: engineer the AI application layer (prompts, structured outputs, retrieval, tool interfaces), build context and retrieval systems, design constraints and fallbacks, and ship reliable, explainable AI features for legal workflows.

Lead Zeno's legal partnerships and legal affairs in Germany by building relationships with law firms, notaries, and legal departments; advise on commercial, regulatory, compliance and product-related legal matters; develop internal policies and governance; collaborate with product and engineering on AI, data protection and responsible product development; represent Zeno in market and shape German go-to-market strategy.

Design and run rigorous experiments for LLM-heavy systems applied to legal reasoning; build reusable experimentation infrastructure, create evaluation datasets where ground truth is incomplete, prototype computational models of law, and collaborate with researchers, engineers, and legal experts to productionize validated approaches.

Design and own durable entity resolution and identity systems for large volumes of unstructured legal data. Build canonical entities, identity graphs with merge/split semantics and provenance, incremental recomputation, reversible decisions, matching and consensus logic, observability, and data quality systems to support explainable, maintainable AI-driven legal search and reasoning.

Lead product-to-market strategy for a legal AI B2B SaaS product: define ICPs, positioning, pricing, launches, sales enablement, customer research, and adoption strategies. Provide cross-functional input to Product, Sales, CS and RevOps and use AI to accelerate research and messaging.