Gen AI Engineer - Liquidity Reporting & Regulatory Compliance

Generative AI Engineer – Liquidity & Regulatory Compliance Location:- Concord, CA 3+ days per week in office Duration:- 6- 12 Months+ Experience in statistical modeling of credit risk (Pricing, BASEL, PPNR, Loss Forecasting, CCAR), marketing risk, quantitative research, Machine Learning, Natural Language Processing (NLP) modelling, Large language modelling (LLM) and Generative Artificial Intelligence (GenAI) modelling. Artificial Intelligence modelling exploration and enhancement by leveraging Large language models like BART, BERT, XLNet, Flan-T5 Job Summary My client is seeking a Generative AI Engineer to join our team and drive AI innovation in the Liquidity Management & Regulatory Compliance space. The ideal candidate will have at least 2 years of hands-on experience in Generative AI and 4+ years of experience in Machine Learning (ML) and Deep Learning (DL). This role will focus on compliance, contract lifecycle management, and regulatory alignment, ensuring that AI-driven solutions meet the highest standards of governance and safety within a highly regulated financial environment. Key Responsibilities: 1. AI Development & Implementation • Design, develop, and deploy Generative AI models (LLMs, NLP, and other deep learning frameworks) to automate and enhance liquidity management, risk assessment, and compliance workflows. • Build AI-driven solutions for contract lifecycle management, optimizing document processing, policy interpretation, and regulatory reporting. • Fine-tune and adapt Large Language Models (LLMs) to align with financial regulations, bank policies, and risk management frameworks. 1. Compliance & Regulatory Alignment • Ensure AI models adhere to financial industry regulations (Basel III, Dodd-Frank, SR 11-7, OCC guidelines, etc.) and internal risk frameworks. • Work closely with Legal, Compliance, and Risk teams to integrate AI solutions while maintaining model transparency and explainability. • Support AI model validation, bias detection, and risk mitigation strategies to align with client’s AI governance policies. 1. AI Model Risk & Governance • Develop rigorous documentation and model audit trails to comply with regulatory requirements. • Monitor AI model drift, fairness, interpretability, and security, ensuring ethical AI usage in financial decision-making. • Implement AI safety and bias mitigation techniques to align with responsible AI principles. 1. Collaboration & Stakeholder Engagement • Partner with Liquidity Risk, Treasury, and Compliance teams to identify AI-driven efficiencies in liquidity forecasting and regulatory reporting. • Work with IT, Data Science, and Risk Management teams to deploy AI solutions in production while ensuring robust monitoring and security. • Contribute to AI research and innovation within, staying ahead of emerging AI regulations and industry best practices. Required Qualifications • Master’s or PhD in Computer Science, Machine Learning, AI, Applied Mathematics, or a related field. • 2+ years of hands-on experience with Generative AI, LLMs, and NLP-based models (e.g., GPT, BERT, Llama, T5). • 5+ years of experience in Machine Learning (ML), Deep Learning (DL), and AI model deployment. • Expertise in compliance-driven AI solutions and working within highly regulated environments (preferably in banking/finance). • Proficiency in Python, TensorFlow, PyTorch, LangChain, Hugging Face, and cloud AI services (AWS, Azure, GCP). • Strong knowledge of AI safety, explainability, and ethical AI principles. • Experience with AI model governance, validation, and bias mitigation techniques. Preferred Qualifications • Prior experience working in liquidity management, risk modelling, or regulatory compliance. • Knowledge of financial regulations related to AI applications in banking (e.g., SR 11-7, OCC AI guidelines). • Hands-on experience with contract lifecycle automation using AI-driven solutions. • Familiarity with MLOps frameworks and model monitoring best practices.