Das ist der Job
Responsibilities Architect and lead the development of agentic AI systems that automate and augment finance workflows.
Darum lohnt es sich
Design and implement multi‑agent systems leveraging LLMs, tool‑use frameworks, and orchestration patterns. Translate cutting‑edge research in LLMs and agentic AI into scalable, production‑ready solutions. Establish guardrails, evaluation frameworks, and responsible AI practices to ensure safe, compliant, and reliable outputs.
Lead the design and implementation of advanced predictive models, including time series forecasting and attrition prediction across customer segments. Develop interpretable, production‑grade models that drive retention strategies and financial planning.
Define and standardize evaluation metrics, validation frameworks, and monitoring systems for model performance and drift detection. Design and build scalable AI/ML systems with a strong emphasis on software engineering best practices. Develop and integrate AI services into internal applications and workflows.
Requirements 8+ years of experience in data science, software engineering, and AI engineering, with significant experience deploying production systems. Proven track record of building production AI systems used at scale. Deep expertise in predictive modeling, including time series forecasting and customer churn modeling.
Advanced proficiency in Python and strong experience with ML/AI frameworks and system design. Hands‑on experience with LLMs, including prompt engineering, fine‑tuning, and evaluation techniques. Strong experience with cloud platforms (preferably AWS), distributed systems, and MLOps practices.
Experience working with financial data and compliance‑aware modeling. Strong software engineering foundation, including API development, containerization (Docker/Kubernetes), and CI/CD pipelines. #J-18808-Ljbffr
