Principal Applied AI Engineer, Finance

Responsibilities

• Architect and lead the development of agentic AI systems that automate finance workflows.
• Design and implement multi-agent systems leveraging LLMs and orchestration patterns.
• Translate cutting-edge research into scalable solutions.
• Establish guardrails and responsible AI practices for safe outputs.
• Lead the design of advanced predictive models for customer behavior forecasting.
• Develop interpretable, production-grade models for retention strategies.
• Design scalable AI/ML systems with emphasis on software engineering best practices.
• Establish MLOps best practices for AI systems deployment and governance.
• Set technical direction for AI/ML initiatives across finance.

• 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.