Our client is creating an AI Factory to modernize finance and accounting across Asia, the US, and Europe. This role is central to designing, building, and rolling out AI-driven automation, machine-learning models, and agentic AI workflows that boost productivity, accuracy, and insight for a 600-person finance team. You'll work with FP&A, Accounting, Tax, Treasury, and IT to take AI solutions from prototype to full-scale production, targeting clear business impact—time savings, fewer errors, better working capital, and improved forecast accuracy.

Key Responsibilities

• Build and deploy AI/ML pipelines to automate core finance processes such as closing, reconciliations, forecasting, and tax analytics
• Develop agentic AI systems using multi-agent frameworks (CrewAI, AutoGen, LangGraph, or equivalents)
• Integrate AI solutions with enterprise platforms like ERP systems, BI tools, Dataiku, Google Vertex AI, and Azure OpenAI
• Create supervised and unsupervised ML models for forecasting, anomaly detection, and fraud/risk analysis
• Fine-tune large language models on finance data while adhering to compliance and governance standards
• Set up monitoring, retraining, and performance management for deployed models
• Convert finance workflows into AI use cases with measurable ROI (e.g., >20% time reduction, >30% accuracy improvement)
• Deliver pilot projects within 90 days and scale them enterprise-wide within 6–12 months
• Partner with process owners to drive adoption and maintain governance
• Ensure solutions meet audit, data privacy, and regulatory requirements
• Incorporate explainability and traceability into all production models

Candidate Profile

• 4–7 years in data science or ML engineering with production-grade deployments
• Experience with AI factory approaches—modular design, reusable components, orchestration frameworks
• Proficiency in Python (pandas, scikit-learn, PyTorch/TensorFlow), SQL, and APIs
• Hands-on work with agentic AI frameworks such as CrewAI, AutoGen, LangChain, or LangGraph
• Cloud deployment experience on Google Vertex AI, Azure ML, AWS SageMaker, or similar
• Proven record of delivering productivity projects with measurable ROI
• Familiarity with finance/accounting processes (forecasting, close, compliance, treasury)
• Knowledge of Dataiku DSS or comparable low-code AI platforms
• Experience with workflow automation tools (Power Automate, UiPath, n8n)