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AI Engineer in Healthcare Startup in Zürich (80-100%)

PlaynVoice

Remote · Switzerland 5d ago

About the role

About

We are a team of entrepreneurs, psychologists, and engineers bringing joy back to therapy. At PlaynVoice, we are reshaping mental health care by combining AI with clinical expertise to make documentation a breeze. In under 2 years, our AI scribe has gone from concept to reality, gaining 500+ users in Switzerland and Germany. We are generating over 20,000 patient notes monthly. We are looking for entrepreneurs; fast, ambitious, and smart individuals who want to take care of the people who take care of our mental health.

Tasks

  • Prompt Engineering & Pipeline Management: Design, iterate, and maintain prompt systems that reliably generate high-quality clinical documentation across a growing number of templates. Build scalable prompt architectures that let us add new output formats without fragmentation.
  • Evaluate & Integrate AI Models: Benchmark and select the best LLM solutions for clinical documentation. Stay on top of the rapidly evolving model landscape and assess new options.
  • Build Evaluation Pipelines: Design practical evaluation processes across our data pipeline from audio and transcription to LLM-generated output. The goal isn't perfection but knowing when output is good enough.
  • Ensure Clinical Output Quality: Work closely with our psychologists and product team to define what "good" looks like, ensuring features meet the real‑world expectations of users.
  • Experiment, Ship, Iterate: Design experiments and data labeling strategies, push them to production, measure real‑world performance, and use the insights to drive the next iteration.

Requirements

  • Prompt Engineering & LLM Expertise: 2+ years of deep experience in systematic prompt engineering, building structured prompt systems that produce reliable outputs at scale.
  • Software Engineering Foundation: Solid engineering skills in Python and cloud infrastructure (we run on Azure). You build reliable, production‑grade systems, not just notebooks.
  • German Language Skills: You need to understand Swiss German to sanity check AI‑generated notes against the original audio. Strong High German for evaluating written clinical output.
  • Pragmatic Startup Mindset: You know that good enough is good enough. You ship fast, iterate based on real‑world feedback, and resist over‑engineering. Ideally you've worked in an early‑stage SaaS company.
  • Clear Communicator: Our team works in English day‑to‑day. You can articulate technical decisions and collaborate effectively across functions.

Benefits

  • Real Impact, Fast: 500+ therapists use our product daily, your work improves their lives within days, not quarters.
  • Unique Problem Domain: Clinical AI at the intersection of Swiss German speech, mental health, and regulatory requirements.
  • Massive Ownership: A team of ~10 means your decisions shape the product directly.
  • Flexibility: Remote‑first with flexible hours and a coworking space in Zürich when you want it.
  • Equity: Meaningful stake in a high‑growth healthtech company.

Application

Please send your CV and 5‑10 sentences about why PlaynVoice; generic applications won't be considered.

Requirements

  • 2+ years of deep experience in systematic prompt engineering, building structured prompt systems that produce reliable outputs at scale.
  • Solid engineering skills in Python and cloud infrastructure (we run on Azure).
  • You need to understand Swiss German to sanity check AI-generated notes against the original audio.
  • Strong High German for evaluating written clinical output.
  • You know that good enough is good enough.
  • You ship fast, iterate based on real-world feedback, and resist over‑engineering.
  • You can articulate technical decisions and collaborate effectively across functions.

Responsibilities

  • Design, iterate, and maintain prompt systems that reliably generate high-quality clinical documentation across a growing number of templates.
  • Build scalable prompt architectures that let us add new output formats without fragmentation.
  • Benchmark and select the best LLM solutions for clinical documentation.
  • Stay on top of the rapidly evolving model landscape and assess new options.
  • Design practical evaluation processes across our data pipeline from audio and transcription to LLM-generated output.
  • Work closely with our psychologists and product team to define what "good" looks like, ensuring features meet the real-world expectations of users.
  • Design experiments and data labeling strategies, push them to production, measure real-world performance, and use the insights to drive the next iteration.

Benefits

Equity

Skills

AzureLLMPython

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