Principal AI Engineer – Automated Channel

Role Overview

• 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.
• Experience with cloud computing platforms (AWS preferred, specifically Bedrock, Sagemaker, Lex, etc.).
• 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

Tech Stack

• AWS
• Cloud
• Docker
• JavaScript
• Python
• PyTorch
• Scikit-Learn
• SQL
• Terraform

Benefits

• Comprehensive benefits
• Differentiated compensation offerings