Beschreibung

In this role, you will take charge of developing and implementing advanced AI solutions, ensuring they are reliable and efficient. Your work will involve collaborating with business partners, optimizing performance, and maintaining compliance in a dynamic environment.

Anforderungen

• •5+ years delivering ML/AI systems in production
• •Expert Python skills
• •SQL/PySpark
• •Spark/Databricks expertise
• •Practical experience with GenAI models and pipelines
• •Hands-on with agent frameworks and tooling
• •RAG expertise: embeddings, vector stores, retrieval, and evaluation approaches
• •LLMOps / MLOps experience: MLflow or similar
• •Feature stores
• •Data/prompt versioning
• •CI/CD (GitHub Actions, Jenkins)
• •Docker
• •Orchestration tools (Airflow, Prefect)
• •Experience designing evaluation and validation frameworks
• •Ability to translate business requirements into production-grade technical solutions
• •Fluent English
• •German is an advantage
• •Knowledge of Responsible AI and regulatory frameworks
• •Banking domain familiarity
• •Software and data engineering foundations
• •APIs (REST/gRPC)
• •Experience with containers and orchestration
• •Kubernetes

Aufgaben

• •Own end-to-end ML/AI/agentic use cases from framing to production
• •Implement MCP and orchestrate LLMs/tools with agent frameworks
• •Build and optimize RAG for precision, recall, and latency
• •Establish LLMOps/MLOps for experiments, versioning, and CI/CD
• •Ensure reliability, safety, and compliance in AI systems
• •Run rigorous offline and online evaluations to monitor performance
• •Optimize performance and cost with usage and cost dashboards
• •Collaborate with business partners to define requirements

Tools & Technologien

Benefits