Co-Founder & CTO | AI Infrastructure Legal Insurance

About You

Are you a systems builder who gets excited about owning the entire technical foundation of an AI company from day one? Do you want to architect infrastructure that legal insurers trust with their most sensitive data and highest-volume workflows? Are you the kind of engineer who ships production systems, sets the bar for the team, and cares as much about customers as about code?

If so, we should talk.

iudexnc AG (Iudex Non Calculat) is a pre-seed AI startup based in Zurich, building cognitive infrastructure that automates coverage checks and case handling for legal insurance companies. Legal insurance is a €16.8B European market serving 150M+ policyholders — and every single case still requires 15–45 minutes of manual review by a human claims handler. We compress that to under 2 minutes.

We already have a paid pilot with a Swiss legal insurer, a working prototype in production testing, active conversations with several major DACH insurers, and two co‑founders: a technical CEO (MSc Applied Math, ETH Zurich; previously built an AI legal tech product with 120+ B2B customers) and a commercial co‑founder with deep DACH insurance and enterprise BD experience. What we need now is a third co‑founder who owns engineering and infrastructure end‑to‑end.

Our long‑term vision: make legal insurance affordable for everyone in the world. Our near‑term path there: become the trusted cognitive infrastructure layer for European legal insurers.

As an Engineering Intern — AI/Data
, you will support the founder across data pipelines, LLM agent workflows, and evaluation infrastructure. Depending on your strengths, you'll go deeper in one area while still getting exposure to the full stack.

• Data pipelines: Help build and improve ingestion and processing pipelines for insurance policy documents, legal texts, and case descriptions (parsing, normalization, structuring).
• AI‑ready structuring: Support chunking, metadata extraction, clause mapping, and schema design so downstream LLM agents work reliably against complex policy wording.
• LLM agent workflows: Prototype and implement agentic LLM workflows for coverage analysis — fact extraction, policy cross‑referencing, exclusion checking, and decision drafting — with attention to accuracy, cost, and latency.
• Search & retrieval: Assist with indexing strategies, embeddings, hybrid retrieval, and relevance tuning for legal and insurance content.
• Evaluation & quality: Build eval sets from real coverage check examples, run experiments, analyze failure cases, and help turn findings into shipped improvements.
• Engineering fundamentals: Write clean Type Script code, add tests where appropriate, and improve observability (metrics/logging) for pipelines and services.
• Collaboration: Work closely with the founder and domain experts; document decisions and share learnings clearly.

• Strong systems engineering and applied AI background. You’ve built and shipped production systems that handle real data at meaningful scale.
• Track record of technical leadership at the right level — ex‑staff/principal engineer at a top company, or ex‑CTO/founding engineer of a B2B AI or infrastructure startup.
• Product taste. You build things that work for users, not just things that are technically interesting.
• High agency: you identify what matters and go do it without waiting for instructions.
• Comfort with ambiguity and early‑stage chaos. You’ve either built something before or operated in an environment where nothing was figured out yet.
• Based in or willing to relocate to Zurich / Western Europe. On‑site collaboration matters at this stage.
• Fluent in English. German is a strong plus.

• Experience with regulated industries (insurance, finance, health, government) where data sovereignty, compliance, and auditability are non‑negotiable.
• Depth in LLM systems, retrieval, evaluation pipelines, or agentic workflows in production.
• Experience with multicloud or multi‑tenant infrastructure for enterprise customers.
• Missionary mindset: you want to build something enduring, not optimize for the next exit.
• Previous founder experience or very…