Job Description
APPLICATION DEADLINE: APRIL 30, 2026
What is the opportunity?
In this role, the Director AI Data Engineering will lead our Machine Learning Engineering Group, focusing on the delivery, operationalization, and continuous maintenance of robust, high-performing AI/ML products in production for our Caribbean Businesses. This critical role combines deep technical expertise in machine learning and MLOps and AIOps, exceptional leadership capabilities, and a profound understanding of the banking industry’s unique challenges and opportunities. The successful candidates has the proven ability to navigate ambiguity to lead in a fast-paced, rapidly evolving technological environment, and proven experience supporting and managing production applications.
What will you do?
- Collaborate closely with Caribbean business leaders, product managers, data scientists, and IT stakeholders across various lines to understand the requirements, define scope and manage expectations.
- Mature MLOps system, embedding automated model training, versioning and monitoring
- Tailor infrastructure and platform support to RBCI needs (i.e. integration and scalability)
- Drive improved CI/CD pipeline for Airflow orchestration
- Implement AI model registry and versioning
- Lead operational AI support: incident management, logging, log monitoring, AIOps, performance tuning, model drift detection, etc.
- Define, communicate, and execute the AI/ML roadmap for Caribbean applications, aligning with overall business vision and emerging AI trends (e.g., Generative AI, Agentic AI, Large Language Models).
- Stay abreast of the latest advancements in AI/ML, particularly in Agentic AI and process automation, and evaluate their applicability and potential for the banking sector.
- Champion ethical and responsible AI principles, ensure all initiatives comply with regulatory requirements specific to the Insurance industry (e.g., OSFI guidelines, privacy regulations).
- Lead, mentor, and grow a team of high-performing Machine Learning Engineers, fostering a culture of technical innovation, collaboration, and continuous improvements.
- Establish and enforce robust monitoring frameworks for all deployed AI/ML productions, ensure the resilience, uptime, and disaster recovery capabilities of all production systems.
- Oversee talent acquisition, performance management, career development and retention for the ML Engineering team.
- Drive the end-to-end development, deployment and operation of robust, scalable, maintainable, and production-ready AI/ML solutions. Ensure the solutions are well-integrated with existing Caribbean systems and data infrastructure.
What do you need to succeed?
Must Have:
- 8+ years of progressive experience in Machine Learning Engineering, AI development or Data Science, with 5+ years in leadership role managing ML engineers or data scientist, with a strong emphasis on production system delivery and operations.
- Proven experience working with or within the Banking industry, demonstrating a clear understanding of its data, processes, and business challenges.
- Exceptional leadership, mentorship, and team-building abilities. Outstanding communication, presentation, and interpersonal skills.
- Demonstrated experience in delivering production-grade AI/ML solutions from concept to production, and production management and support.
- Experience with process automation initiatives and a strong understanding of Agentic AI paradigms.
- Expertise in programming languages commonly used in ML (Python is essential, others like Java, Scala, R are a plus).
- Proficiency with ML frameworks, libraries (e.g., PyTorch, TensorFlow, AirFlow, Hugging Face).
- Strong understanding of MLOps principles, tools and platforms (e.g., MLflow, AWS SageMaker, Azure ML).
- Solid experience with cloud platforms for ML infrastructure, modern data architecture, and scalable computing.
- Demonstrated commitment to continuous learning and staying current with AI/ML advancements.
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Electrical Engineering or a related quantitative field
- Master’s or Ph.D. preferred
Nice to Have
- Knowledge of data engineering tools, such as Apache Beam, Apache Spark, or AWS Glue
- Familiarity with agile development methodologies and version control systems (e.g., Git)
- Certifications including AWS Certified Machine Learning – Specialty, Specialized MLOps Certifications, AI Engineering Professionals.
- Adaptability, Critical thinking and growing mindset
- Team contributor and care about team members
What’s in it for you?
We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.
- A comprehensive Total Rewards Program including bonuses and flex