Job Description

? About You
Do you love making search actually work well for the user? Are you hands-on with ranking algorithms, query understanding, and excited to ship improvements that users feel the same day? Do you enjoy building pragmatic, low-latency, cost-aware solutions for AI-assisted legal research (where citations, precision, and traceability matter)? If so, we'd love to hear from you.
? About Omnilex
Omnilex is a young dynamic AI legal tech startup with its roots at ETH Zurich. Our passionate interdisciplinary team of 14+ people is dedicated to empowering legal professionals in law firms and legal teams by leveraging the power of AI for legal research and answering complex legal questions. We already stand out with handling unique challenges, including our combination of external data, customer-internal data and our own innovative AI-first legal commentaries.
Tasks
?? Your Responsibilities
As an AI Engineer - Legal Search Optimization, you will focus on building and shipping retrieval, reasoning and context engineering that powers our legal research experience.

• Retrieval & ranking: Implement and iterate domain-sepcific retrieval and reranking algorithms going beyond the standard ones, including knowledge-graphs and custom workflows.
• LLM-powered products: Design and build robust, production-grade LLM systems and chatbots.
• Signals & features: Design scoring features from citations, authority, recency, jurisdiction, section/paragraph structure, and intra-doc anchors.
• Practical considerations: Carefully evaluate decisions like API vs. self-hosted; add batching, early-exit, and caching to control cost/latency.
• Evaluation that guides shipping: Define offline eval sets, run quick ablations, and watch production feedback and dashboards.
• Search infrastructure: Tune indices, analyzers, and embeddings; manage recall/precision trade-offs and de-duplication/near-duplicate suppression.
• Cost & performance: Keep token usage, GPU/CPU time, and indexing costs under control with caching, pre-computation, and fallbacks.
• Collaboration: Work closely with legal experts to turn user pain points into ranking features; document decisions and share clear playbooks.

Requirements
? Minimum qualifications

• Strong hands-on experience improving search/retrieval systems (hybrid retrieval, reranking, or query understanding) in production.
• Proven experience in building and deploying LLM-based products from prototypingto production
• Solid algorithms background (data structures, complexity, graph theory, statistics), IR/NLP intuition, and practical SQL skills.
• Proficiency in TypeScript/Node.js (our core stack).
• Experience with one or more of: Azure AI Search, pgvector/PostgreSQL, OpenSearch/Elasticsearch, or similar.
• Familiarity with modern embedding models and cross-encoders for reranking; ability to reason about latency, throughput, and quality trade-offs.
• Ownership mindset, clear communication, and bias for action.
• Proficiency in English;
• Availability full-time. On-site in Zurich at least two days per week (hybrid).

? Preferred qualifications

• You have a Swiss work permit or EU/EFTA citizenship.
• Working proficiency in German (many sources are in German and we talk to German-speaking customers).
• Experience with evaluation pipelines (AI as judge, human-in-the-loop labeling, inter-annotator agreement, error analysis) applied pragmatically.
• Practical knowledge of sparse methods (BM25+/BM25L/SPLADE), dense models (e5/BGE/ColBERT-style), and semantic re-ranking.
• Experience deploying/operating small models or services (Docker; basic Kubernetes or serverless is a plus).
• Familiarity with our stack: Azure / NestJS / Next.js.
• Knowledge and experience with legal systems, in particular Switzerland, Germany, USA ????

Benefits
? Benefits

• Direct impact: your ranking and retrieval changes immediately improve result quality and user trust.
• Autonomy & ownership: Shape our legal research pipeline, across multi-facetted user intention understanding, dynamic retrieval and reranking
• Team: Work with a sharp, interdisciplinary team at the intersection of AI, search, and law.
• Compensation: CHF 7'000-11'000 per month + ESOP (employee stock options), depending on experience and skills.

We're excited to hear from candidates who are passionate about making legal search fast, accurate, and trustworthy. Apply today by pressing the Apply button.
Omnilex

Skills Required