AI Engineer - Automated Channels Transformation

Essential Duties And Responsibilities

• Design, develop, and implement AI and machine learning systems that address specific business challenges and deliver measurable value.
• Create and maintain model documentation, ensuring transparency in methodologies and approaches.
• Research, test, and apply state-of-the-art generative AI models and/or solutions for potential use.
• Create agentic AI systems capable of autonomous reasoning, planning, and tool utilization for complex task completion.
• Develop comprehensive evaluation frameworks to assess model performance, detect hallucinations, and ensure output quality.
• Stay current with emerging AI/ML technologies, frameworks, and methodologies.
• Contribute to establishing best practices for AI development and deployment.
• Sets enterprise-wide technical standards by defining reference architectures, chairing design reviews, and approving model lifecycle gates (e.g., data sourcing, bias audits, drift monitoring).

Analytics and Insights

• Extract meaningful patterns and insights from complex, multi-dimensional data sets.
• Apply advanced analytics including predictive modeling, machine learning, and optimization techniques.
• Translate business questions into well-defined analytical problems with clear objectives.
• Design and execute experiments with statistically valid methodologies and evaluation criteria.
• Develop specialized analytics for banking-specific use cases while maintaining compliance with financial regulations.

Collaboration and Communication

• Leads projects or processes with limited supervision, applying advanced knowledge to solve complex problems and coach or review the work of lower-level professionals.
• Acts as a resource for colleagues, influencing technical direction and standards across multiple products or platforms.
• Drives cross-team technical initiatives and mentors Lead Engineers, ensuring integration, scalability, and compliance across multiple products and platforms.
• Partner with cross-functional teams to understand business requirements and translate them into technical solutions.
• Effectively communicate complex technical concepts to non-technical stakeholders.
• Present findings, recommendations, and insights to business teams in accessible formats.
• Work with software engineers, cloud engineers, data engineers, and data scientists to integrate AI solutions into existing systems and products.
• Work with compliance and security teams to ensure AI systems meet banking regulatory requirements.

Education And Experience

• 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).
• Experience designing observability systems for AI applications.

Position not available for immigration sponsorship

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