Key skills
AILLMLarge Language ModelsRAGAgenticLangGraphAgile
About this role
Role Overview
- Build and scale AI systems: Design, implement, and optimize core components of our agentic AI architecture with a focus on performance and reliability
- Develop agentic workflows: Build on multi-agent systems using LLMs, orchestration frameworks (LangGraph), RAG, and context engineering
- Ship advanced AI features: Develop innovative capabilities such as layout optimization, structured reasoning flows, and multimodal workflows
- Contribute to product evolution: Collaborate closely with product and engineering teams to shape features through experimentation and rapid iteration
- Drive continuous improvement: Help refine best practices for evaluation, deployment, monitoring, and scaling of AI systems in production
Requirements
- Entrepreneurial mindset with strong ownership, creative thinking, and a pragmatic approach to building and shipping solutions quickly
- At least 2 years of experience building production-grade AI systems, with a strong focus on Large Language Models
- Proven experience designing and delivering agentic architectures and multi-step reasoning pipelines
- Hands-on experience with orchestration frameworks such as LangGraph and retrieval systems (RAG/REC)
- Strong understanding of prompt engineering, evaluation strategies, and LLM reliability optimization
- Bonus: Experience with fine-tuning LLMs or working with multimodal / visual AI models
- Residency in Berlin or the surrounding area
- Fluency in English, our primary business language
- Availability to start on short notice
Benefits
- Attractive compensation package including a competitive monthly salary and VSOP equity in a fast-growing AI startup
- Flexible hybrid work model with two office days per week, complemented by regular team events
- High level of ownership and creative freedom within a young, ambitious team, with the opportunity to help build the company from the ground up
- Agile, output-driven work culture with minimal meetings, low administrative overhead tasks, and direct impact on the product
- Early-stage startup exposure, including building and scaling core product functions while we onboard large enterprise customers