The Principal AI Engineer architects and implements artificial intelligence and machine learning systems that address diverse business challenges throughout the Bank, with a strong focus on research and experimentation of generative AI models and agentic systems.
This role involves conducting rigorous data analysis, performing statistical evaluation, designing experimental frameworks, and developing algorithms that effectively leverage both structured and unstructured data.
The AI Engineer creates solutions that range from on-demand analytics to fully integrated software systems, working closely with cross-functional teams to align technical solutions with business requirements.
Staying apprised and educating senior leaders on emerging AI trends, risks, and opportunities.
Responsible and accountable for risk by openly exchanging ideas and opinions, elevating concerns, and personally following policies and procedures as defined.
Requirements
Bachelor's degree in Computer Science, Statistics, Data Science, Mathematics, or related technical field; Advanced degree preferred but not required.
6+ years of experience developing and deploying machine learning or AI solutions in production environments.
Strong programming skills with proficiency in Python; familiarity with JavaScript and SQL.
Expertise in generative AI techniques including prompt engineering, fine-tuning, retrieval-augmented generation (RAG), evaluation frameworks, tool integration, and agentic system design.
Skilled in data visualization and storytelling, effectively communicating complex analytical insights in clear, actionable formats for technical and non-technical audiences.
Experience with machine learning frameworks (PyTorch, scikit-learn, Hugging Face).
Practical knowledge of deep learning, neural networks, and traditional ML algorithms.
Familiarity with model optimization techniques including quantization and distillation.
Knowledge of AI orchestration frameworks (LangChain, LlamaIndex, MCPs, etc.).
Proficiency with version control systems (Git/GitHub)
Understanding of CI/CD pipelines and DevOps practices
Experience with containerization and Infrastructure as Code (Docker, Terraform)
Knowledge of data structures, algorithms, and software design principles
Experience designing observability systems for AI applications
Communicates clearly and builds consensus across teams
Mentors colleagues and promotes knowledge sharing
Excellent written and verbal communication skills
Strong analytical thinking and problem-solving abilities
Ability to manage time effectively and prioritize competing demands
Self-motivated with demonstrated capacity to work independently
Experience working in Agile environments
Proficiency with Microsoft Office suite (Word, Excel, PowerPoint)
Understanding of ethical considerations in AI deployment