AI Process Engineer – Zürich

Full-time Zürich Posted 18 May 2026

A senior firm, sized like a startup.

Convolving is a Swiss-based AI services firm running fixed-fee sprints for clients across five regulated industries. Delivery is partner-led on every engagement, and the team has shipped 30+ engagements to date. We pair tenured functional operators with AI-native engineers and a Technical Program Manager on every sprint, so the redesign lands in production rather than in a slide deck.

Engagements run 3 to 12 weeks at a flat fee. No retainer creep, no timesheet tracking, no change orders. When the artifact is shipped and adopted, the engagement closes. The hiring bar is senior across the firm: we do not build pyramids and we do not staff with juniors.

The engineer who ships into the client’s stack.

This is the engineering seat that puts the workflow into production. We hire AI Process Engineers out of two profiles: AI-native engineers from a research or applied-AI background who want client-facing work, and senior backend or platform engineers who have moved into shipping LLM systems in the last 18 to 36 months.

Your seat sits inside the client’s environment for the duration of the sprint. You ship retrieval pipelines, evals, agentic systems, and integration plumbing inside Azure, AWS, GCP, or on-prem footprints. The Functional Expert tells you where the controls are; the Technical Program Manager owns the cadence. You own the artifact.

First 90 days: pair with a senior engineer on two live sprints, take engineering lead on a third, and contribute to the internal eval and retrieval template library. By month six you are running one engagement at a time as the engineering owner, with a junior engineer or research apprentice paired in.

The work, week to week.

• Build retrieval pipelines, evals, and agentic systems inside the client’s production environment across Claude, OpenAI, and Gemini APIs.
• Stand up evaluation suites against the client’s real workflow data, not toy datasets, and treat the eval as the unit of progress.
• Wire the redesigned workflow into the client’s existing stack (ERP, CRM, document store, ticketing, EHR, or function-specific systems) using their auth and data-residency posture.
• Own the controls and observability layer: traceability of every model call, structured logs, escalation paths for hallucinated or low-confidence output.
• Sit beside the Functional Expert in discovery and prototype against the actual exception cases they surface, not the happy path.
• Hand over a maintainable artifact at sprint close: documented retrieval graph, eval suite, runbook, and on-call rotation handover to the client’s engineering team.
• Feed every engagement’s patterns back into the firm’s internal template library.

The shape of the hire.

• Five or more years of software engineering experience, with at least 12 months shipping LLM systems against production traffic or a regulated workflow.
• Working fluency with at least two of:
  Claude, OpenAI, Gemini APIs. Strong opinions about retrieval, evals, and structured output.
• Comfort across one major cloud (Azure, AWS, or GCP) including identity, networking, and data-residency primitives.
• Python strong;
  Type Script or Go a plus. SQL and basic data-modelling fluency.
• Direct client-facing experience or strong indicators that you can do it: presented at conferences, ran an open-source project with users, mentored a team.
• Allergic to abstraction-for-its-own-sake. We ship working systems, not framework essays.
• Swiss work permit or EU/EFTA citizenship. Based in our Oberrieden, ZH office; one or two days remote per week.

Useful, not required.

• Prior forward-deployed engineering experience at Palantir, Tenex, or a similar firm.
• A…