🌟 About You

Do you enjoy taking a strong AI product and making it work beautifully inside a customer’s real-world environment; messy data, unique workflows, strict permissions, and high expectations? Are you hands-on, pragmatic, and happiest when you can ship an improvement that a specific legal team immediately feels?

You’re comfortable being the “technical bridge” between customers, legal experts, and the core product team: you diagnose issues, propose solutions, implement them, and leave behind clean playbooks so the next deployment gets easier.

🚀 About Omnilex

Omnilex is a young dynamic AI legal tech startup with its roots at ETH Zurich. Our interdisciplinary team (12+ people) empowers legal professionals by leveraging AI for legal research; combining external data, customer-internal data, and our own AI-first legal commentaries.

Tasks

🛠️ Your Responsibilities

As an AI Solutions Engineer, you will focus on deploying, tailoring, and operationalizing Omnilex’s legal search + LLM workflows for customers; while feeding the best learnings back into the product.

Customer deployments & adaptations (core of the role)

• Own technical onboarding for new customers: data ingestion, indexing, metadata mapping (jurisdiction, authority, recency), and validation.
• Configure and adapt retrieval + reranking pipelines to customer needs (practice area focus, doc structure, internal taxonomies, “what good looks like”).
• Implement customer-specific workflows: templates, filters, jurisdiction defaults, citation behavior, permission-aware retrieval, and custom result layouts.

LLM workflows that are production-safe

• Tailor prompting / context engineering to customer requirements (traceability, citation style, explanation depth, fallback behavior).
• Implement safeguards: provenance, source grounding, “no-citation → no-claim” behaviors, and “confidence/uncertainty” patterns aligned with legal risk.

Evaluation & iteration in the field

• Build lightweight customer-specific eval sets (gold questions, acceptance criteria, “must-not-fail” cases).
• Run fast error analyses and ship fixes: query understanding tweaks, reranker tuning, chunking strategy, dedupe suppression, caching, and retrieval routing.

Performance, cost, reliability

• Keep latency and costs under control with caching, batching, early exit, and sensible fallbacks.
• Monitor quality + usage signals; turn customer feedback into concrete improvements and measurable acceptance checks.

Collaboration & knowledge transfer

• Work closely with Customer Success + legal experts to translate pain points into system changes.
• Document integrations and “deployment recipes” so solutions become reusable product capabilities over time.

Requirements

✅ Minimum qualifications

• Strong hands-on experience building or adapting search/retrieval systems in production (hybrid retrieval, reranking, query understanding, indexing).
• Proven experience taking LLM workflows from prototype to reliable production use.
• Proficiency in TypeScript/Node.js (our core stack).
• Experience with one or more of: Azure AI Search, pgvector/PostgreSQL, OpenSearch/Elasticsearch (or similar).
• Practical engineering instincts: debugging, performance tuning, careful handling of edge cases, and clear operational thinking.
• Strong communication skills and comfort working directly with customers (technical deep-dives, explaining trade-offs, writing playbooks).
• Proficiency in English; full-time availability.
• Hybrid presence: on-site in Zurich at least two days per week.

🎯 Preferred qualifications

• German proficiency (many sources and customer interactions are German-speaking).
• Experience integrating customer data sources / document pipelines (connectors, ETL, access controls).
• Experience with pragmatic eval pipelines (human-in-the-loop labeling, inter-annotator agreement, lightweight dashboards).
• Familiarity with sparse + dense retrieval methods (BM25 variants).
• Experience operating services (Docker is a plus).
• Familiarity with our stack: Azure / NestJS / Next.js.
• Knowledge of Swiss / German / US legal systems is a plus.

Benefits

🤝 Benefits

• Customer-visible impact: your work directly determines whether customers trust the product in daily legal workflows.
• Autonomy & ownership: you’ll own deployments end-to-end and shape repeatable “solution patterns.”
• Fast learning loop: see real-world failure modes early; help steer product priorities with evidence.
• Compensation: CHF 7’000–11’000 per month + ESOP, depending on experience and skills.

We’re excited to meet builders who enjoy getting close to customers and shipping improvements that make legal research faster, more accurate, and more trustworthy. If you like turning real-world pain points into robust, repeatable solutions, we’d love to hear from you. Apply by pressing the Apply button.