AI Engineer at PlaynVoice leveraging AI to improve clinical documentation for mental health care. Collaborate with a diverse team to shape the future of therapy support.
Responsibilities
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.
Data & AI Engineer owning end - to - end lifecycle of data - driven AI applications for Formula E. Bridging data architecture with intelligence and leveraging Google Cloud technologies for high impact.
AI Developer at Hollis, leading the design and deployment of AI capabilities across the business. Focuses on creating a proprietary AI platform and improving productivity through data - driven solutions.
Applied AI Engineer helping to build and deploy AI - enabled software solutions for enterprise customers. Working in a fast - paced environment with a high degree of ownership and collaboration.
AI Engineer collaborating with AI recruiters Alex and Mila to connect candidates to suitable job opportunities. Handling important communication and application processes effectively.
AI Engineer automating workflows across enterprise systems. Delivering AI solutions to enterprise customers in Bangkok with strong coding and hands - on experience.
Lead AI Engineer building production - ready AI applications, deploying them on Azure Databricks in Bengaluru. Collaborating with data scientists and platform engineers for scalable AI solutions.
Lead AI Engineer developing AI - powered systems at Capital One. Collaborate with cross - functional teams to enhance customer interactions and product offerings.
Applied AI Engineer responsible for building and maintaining AI agents for Zello's voice - first communication platform. Collaborating with the Data & AI team to drive continuous improvements.
Lead AI Engineer at ZEISS developing agent - based applications and AI solutions. Collaborate with interdisciplinary teams to showcase AI innovations and ensure compliance with organizational standards.