Engineering · Zurich HQ · FullTime · Mid level
This is a backend engineering role on a new data platform, where core design choices are still open and the engineer helps make them. A strong candidate has shipped and run stateful backend systems, understands databases well, and can reason from first principles when information is incomplete. Comfort with ambiguity and end to end ownership matters more than a checklist of tools.
How it fits the AI era
The platform serves legal teams that use AI search and agentic workflows, so the backend must handle heavy model driven workloads reliably. Much routine coding speeds up with AI tools, while judgment about correctness, reliability and performance stays with the engineer. Deciding how systems are structured and operated in production remains human work.
How it builds AI experience
The role offers exposure to optimizing large language model workloads for quality and cost, which is a useful skill to build. Candidates can prepare by studying how LLM calls are batched, cached and scheduled, and by practicing with workflow engines or job schedulers. Understanding how retrieval and agentic pipelines depend on storage and orchestration helps connect the work to what the company builds for legal teams.
Worth showing
- Stateful backend systems
- SQL and NoSQL databases
- Distributed systems basics
- Production reliability focus
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About DeepJudge
DeepJudge provides AI-powered enterprise search and agentic AI workflows for legal teams, per the company.
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