# AI Program Lead at Apheris

> Remote · region unclear · Staff · Other · open. Source: https://alderhq.app/jobs/personio%3Aapheris%3A2811725 (read 2026-11-09).

## Facts (observed)

- Company: [Apheris](https://alderhq.app/companies/apheris)
- Location text: Remote (UTC +/- 2 hrs)
- Where it can be done from (inferred): Remote · region unclear (evidence: "Location: Remote (UTC +/- 2 hrs)")
- Posted: 2026-09-23 (46 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://apheris.jobs.personio.de/job/2811725

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### About Apheris

Leading pharma companies train higher-performing models on this data without ever exposing it, and we deliver those models through Apheris Foundry, our drug discovery platform.

### About the role

This is a high-ownership, high-visibility seat. You'll be the person top pharma scientists call when something needs to move, and the person who turns a network from concept to models running in production. Our networks are scaling fast and the work is only getting bigger from here.

### About you

You've run complex, multi-party programs before and you know the difference between managing a process and actually owning an outcome.

We're looking for someone with 3+ years in scientific or technical program management, alliance management, or customer-facing delivery of scientific software, who wants real ownership over how our networks and our platform land with some of the biggest names in pharma.

### What we offer you

Competitive compensation with early-stage virtual share options, a remote-first setup with real flexibility on where you work, and genuine investment in your wellbeing: mental health support, a work-from-home and co-working budget, a learning budget, and generous holiday. We bring the team together three times a year, in Berlin and elsewhere in Europe.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/personio%3Aapheris%3A2811725 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.