Software Engineer - Orchestration

present of AI; Zürich; Hybrid; CHF 120,000 - 160,000; Full time

Job summary

present of AI is seeking a mid-level Backend Engineer in Zurich to contribute to a new data platform where core design choices are still open. You will own production systems and help push reliability and scale in a hands-on role.

Ideal candidates have shipped stateful backend services, understand SQL and NoSQL databases, and can reason from first principles when information is incomplete. End-to-end ownership matters more than a checklist of tools.

Qualifications

• Experience shipping and running stateful backend services.
• Strong database knowledge (SQL/NoSQL).
• Ability to reason from first principles with incomplete information.
• End-to-end ownership mindset.

Responsibilities

• Own design and operation of production-grade backend systems.
• Contribute to the data platform supporting AI workloads.
• Collaborate on architecture decisions for reliability and scale.

Skills

Stateful backends

SQL databases

NoSQL databases

Distributed systems

Job description

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.