Lead AI Engineer
LMN
Python
Senior Validator Vice President – Artificial Intelligence Non-Model Risk Review Team
Citi
full-time
Posted on:
Origin: • 🇺🇸 United States
Visit company websiteSalary
💰 $125,760 - $188,640 per year
Job Level
Senior
Tech Stack
Python
About the role
- Manage a portfolio of Generative AI and NLP models, with a focus on operational efficiency and process automation.
- Perform model validations, annual reviews, ongoing monitoring, model limitation remediation, and supervisory/peer reviews for the assigned portfolio.
- Evaluate both technical and functional aspects of Generative AI and NLP models, including model assumptions, conceptual soundness, mathematical formulation, calibration, and performance.
- Assess the functional application of these models for regulatory and business purposes.
- Conduct in-depth reviews of model development documentation, identify shortcomings, execute validation tests, and communicate findings to senior stakeholders.
- Prepare comprehensive validation reports and manage model risk on an ongoing basis.
- Conduct research on emerging techniques in Generative AI, NLP, and machine learning to ensure the team remains at the forefront of innovation.
- Develop model validation guidelines and testing playbooks to standardize best practices.
- Present validation findings and recommendations to senior management and other stakeholders, ensuring clear communication of complex technical concepts to non-technical audiences.
- Collaborate with cross-functional teams to develop and implement Generative AI solutions, driving innovation and operational excellence.
- Contribute to the development of Generative AI Use Cases for Model Risk Management.
Requirements
- Minimum of 4+ years of experience in AI/ML model development, validation, or implementation, with a strong focus on NLP.
- Hands-on experience with Generative AI models, including development, implementation, Retrieval-Augmented Generation (RAG), and prompt engineering.
- Advanced programming skills in Python, with proficiency in data analysis, interpretation, and visualization.
- Deep understanding of model risk management frameworks and regulatory requirements, with the ability to apply these principles effectively in practice.
- Proven ability to manage multiple projects simultaneously, demonstrating strong organizational and project management skills.
- Strong communication skills, with the ability to articulate complex technical findings to non-technical stakeholders and senior management in a clear and concise manner.
- Demonstrated ability to learn and apply new techniques in AI/ML, particularly in Generative AI and NLP.
- Education: Master’s or Ph.D. degree in a quantitative field such as Data Science, Statistics, Mathematics, Finance, Computer Science, or a related discipline.
