Backend Engineer (AI/ Legal Tech)

Saga is an AI platform built by lawyers and technologists, designed to manage the entire lifecycle of legal work - from research and contract analysis to project management and knowledge sharing. Founded in Norway and built for the legal profession from day one, Saga integrates with local legal sources across jurisdictions and is currently available in 12 languages. In just 18 months, the company has grown to 71 employees, 5000 users across 16 countries. With market leadership in Norway and the Netherlands, and active expansion across Europe, Saga is scaling fast - and looking for people who want to build something that matters.

Your role as Backend Engineer
As a Backend Engineer, you will design and build the systems that power AI-driven legal workflows. You'll own backend services end-to-end, from TypeScript/Node.js REST APIs and data models to deployment and ongoing operation. Working closely with engineering, legal, and product teams, you'll develop scalable features including document processing, semantic search, vector search, and RAG-based capabilities powered by LLMs from providers such as OpenAI, Anthropic, and Google. You'll help shape technical architecture while balancing innovation with practical improvements to existing systems. Success in this role comes from delivering reliable, secure, and maintainable systems that create measurable impact for customers.

What you'll be doing

• Design, build, and maintain backend services, REST APIs, and data models using TypeScript and Node.js

• Develop document ingestion, processing, semantic search, vector search, and RAG-based systems leveraging LLMs from providers such as OpenAI, Anthropic, and Google

• Build and operate asynchronous processing pipelines, background workers, and long-running jobs

• Improve performance, reliability, scalability, and security across distributed, multi-tenant systems and databases

• Collaborate with engineering, legal, and product teams to deliver customer-facing features and contribute to architectural decisions

• Monitor, maintain, and continuously improve production systems and platform capabilities