Ai Engineer

Experteer Overview In this role, you will bridge AI prototypes and customer-facing features, transforming proven models into reliable, production-ready services.You'll work with Data Science, ML Engineering, and Platform teams to accelerate time-to-market for AI features.You'll design observability, metrics, and scalable architectures to support high-traffic deployments.This is a hands-on role focusing on RAG, autonomous agents, and multi-channel experiences to enhance the bank's conversational assistant.Join a cross-disciplinary team shaping the future of customer interactions at N26.Compensaciones / Beneficios* Drive rapid prototype-to-production transitions for AI/LLM features* Productionize AI services including LLM-powered features and autonomous agents in a high-traffic environment* Build observability, metrics, tracing, and logging for AI features; implement A/B testing for models/prompts* Architect data pipelines, APIs, and orchestration to support scalable AI services* Collaborate with Platform Engineering to design custom AI components (MCP servers, Agent interactions) and leverage foundational models* Implement advanced AI techniques (RAG, MCP, A2A) and refine deployment approaches* Contribute to discovery of new AI use cases by assessing constraints, data availability, and feasibility in production* Ensure reliable monitoring, logging, failure handling across the lifecycleResponsabilidades* Proven experience deploying ML/LLM-based applications in production* Backend engineering proficiency with Python and Kotlin; API design and microservices* Applied AI/MLOps experience with LLM frameworks, vector databases, prompt engineering, and RAG* Data engineering experience with data pipelines and feature stores* Cloud infrastructure knowledge (AWS) and experience with containerized services (Kubernetes, Docker)* Experience with model/LLM serving platforms (SageMaker, Bedrock, Vertex AI) is desirable* Outcome-driven mindset focused on delivering tangible business impactRequisitos principales* competitive personal development budget* work from home budget* discounts for fitness u**** wellness* language apps* public transportation subsidies* premium N26 bank account subscriptions for you and family

• Proven experience deploying ML/LLM-based applications in production
• Backend engineering proficiency with Python and Kotlin; API design and microservices
• Applied AI/MLOps experience with LLM frameworks, vector databases, prompt engineering, and RAG
• Data engineering experience with data pipelines and feature stores
• Cloud infrastructure knowledge (AWS) and experience with containerized services (Kubernetes, Docker)
• Experience with model/LLM serving platforms (SageMaker, Bedrock, Vertex AI) is desirable
• Outcome-driven mindset focused on delivering tangible business impact