AI Feature Engineer — LLMs & NLP for SaaS

Try&Hire; Hurden; Hybrid; CHF 120.000 - 170.000; Vollzeit

Zusammenfassung

Try&Hire in Switzerland seeks an AI/ML engineer to design, develop and deploy scalable AI features for a web-based business software product. You will work in an AI feature team with high personal responsibility and collaborate closely with cross-functional colleagues.

The role emphasizes hands-on work with LLMs, RAG, prompt engineering and cloud platforms, in a hybrid setup (80–100% workload). Initial 3–6 months are interim, with the option of a permanent position afterward.

Qualifikationen

• University degree in computer science or related field.
• Experience as AI/ML engineer or fullstack engineer building scalable AI features.
• Hands-on experience with cloud environments and AI platforms.
• Proven experience deploying LLMs for real business applications.
• Advanced Python programming skills, AI/ML libraries, backend and databases.
• Familiarity with SaaS architectures and API integrations; basics in containers and CI/CD.
• Fluent English; German a plus.

Aufgaben

• Work in an AI feature team with high personal responsibility.
• Design, develop and implement scalable AI-powered features.
• Work with large language models for NLP, conversational AI and generative use cases.
• Collaborate with cross-functional teams to design AI-driven features and applications.
• Drive innovation by researching the latest AI technologies and proposing new approaches.

Kenntnisse

AI engineering

Python programming

Backend development

Cloud platforms

RAG & LLM deployment

Prompt engineering

APIs & SaaS

CI/CD basics

English fluent

German a plus

Ausbildung

University degree in computer science or related field

Tools

GCP

Vertex AI

LangChain

LlamaIndex

MongoDB

Redis

Angular

PHP

Jenkins

Jobbeschreibung

Try&Hire in Switzerland seeks an AI/ML engineer to design, develop and deploy scalable AI features for a web-based business software product. You will work in an AI feature team with high personal responsibility and collaborate closely with cross-functional colleagues.

The role emphasizes hands-on work with LLMs, RAG, prompt engineering and cloud platforms, in a hybrid setup (80–100% workload). Initial 3–6 months are interim, with the option of a permanent position afterward.