AI/ML Engineer Regulatory Reporting Vice President

• Build unsupervised and semi-supervised ML models (e.g., Isolation Forests, Autoencoders) to scan millions of transactional records for outliers
• Design RAG (Retrieval-Augmented Generation) pipelines to 'chat' with unstructured data (Credit Agreements, Loan Docs) and extract key regulatory attributes (Maturity Dates, Collateral Clauses)
• Build 'Agentic' workflows where GenAI proactively suggests mapping logic or identifies the root cause of a break, requiring only a 'thumbs up/down' from the human SME
• Build 'Explainability' (XAI) into every model
• Create Validation Interfaces: Build simple UIs (using Streamlit or React) where business users can see the Model's Prediction side-by-side with the Source Document to rapidly approve/reject the finding
• Work with Model Risk Management (MRM) to establish a 'fast-track' validation framework for non-deterministic GenAI models
• Act as the 'AI Evangelist' to the Operations/Finance teams, demonstrating how AI assists them rather than replacing them

• 6+ years in Data Science/Engineering
• Deep experience with Scikit-learn, TensorFlow, or PyTorch
• Hands-on experience with LLM orchestration frameworks (LangChain, LlamaIndex) and Vector Databases (Pinecone, Milvus, or pgvector)
• Experience building tools like Streamlit or Gradio for rapid prototyping of human-review interfaces

Experience in Financial Services (specifically Fraud Detection, AML, or Risk Modeling)