What are the responsibilities and job description for the AVP, Artificial Intelligence position at Credit One Bank?
Description
Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
Core AI Concepts And Technologies Required
Programming & Tooling
Position Summary
The Assistant Vice President of Artificial Intelligence (AVP of AI) is responsible for leading delivery and execution of AI and machine learning capabilities within a regulated banking, credit card, and financial services environment. Reporting to the VP of AI, this role acts as a hands-on technical leader and people manager for AI Engineers, ensuring AI solutions drive fraud prevention, credit risk management, customer experience personalization, and operational efficiency while meeting regulatory, privacy, and model risk requirements.
Essential Job Functions
- Lead development and deployment of AI/ML and Generative AI solutions for fraud detection, credit scoring, underwriting, AML, and customer engagement.
- Serve as technical authority for model architecture, feature engineering, training pipelines, and inference services.
- Manage and mentor AI Engineers and ML practitioners; provide code and design reviews.
- Implement AIOps/MLOps and model governance practices aligned with banking regulations and internal Model Risk Management (MRM) standards.
- Partner with Risk, Compliance, Legal, Cybersecurity, and Data teams to ensure Responsible AI adoption.
- Oversee model validation, explainability, bias testing, and audit readiness.
- Collaborate with product and business leaders to translate financial use cases into scalable AI solutions.
Core AI Concepts And Technologies Required
- Machine Learning & Modeling
- Supervised, unsupervised, reinforcement learning
- Deep learning (CNNs, RNNs, Transformers)
- Natural Language Processing (NLP) & LLMs
- Generative AI (diffusion models, fine-tuning, RAG)
- AI Engineering & MLOps
- AI Engineering & MLOps
- Model training, deployment, monitoring, and retraining
- Feature stores, vector databases, and model registries
- CI/CD pipelines for ML (MLOps)
- GPU/accelerator compute architectures
- Cloud & Infrastructure
- Azure AI, Azure ML, AWS Sagemaker, or Google Vertex AI
- Kubernetes, containerization, microservices
- Data platforms (Databricks, Snowflake, Synapse)
- Responsible AI & Governance
- Model explainability (SHAP, LIME)
- Fairness, bias detection, model risk controls
- Privacy-preserving ML techniques (differential privacy, federated learning)
- Python, PyTorch, TensorFlow, JAX
- LangChain, semantic search, vector embeddings
- Prompt engineering & LLM orchestration frameworks
- Excellent communication, problem-solving, and project management skills
- Ability to collaborate effectively and follow up ensure achievement of deadlines, outcomes and results.
- Demonstrate company core values of excellence, ownership, collaboration, and integrity.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or related field.
- 5-8 years of experience in AI/ML or data science.
- Experience working with large-scale financial or transactional data is preferred.