- Collaborate closely with sales teams to understand client needs and objectives.- Conduct comprehensive technical product demonstrations to stakeholders at all levels, effectively translating complex concepts into actionable insights.- Design scalable and cost-effective solutions that align with client goals.- Advise clients on technology best practices and guiding them through the decision-making process.- Act as a key liaison between technical and non-technical stakeholders, ensuring clear communication and alignment on project goals and deliverables.- Build and maintain strong client relationships throughout the sales cycle.- Collaborate with cross-functional teams to ensure seamless project handoffs.- Engage in continuous learning to stay ahead of emerging technologies, trends, and industry standards.

- Manage and resolve advanced requests/questions and independently answer and resolve calls from clients- Mentor and manage more junior members on the Technical Support Team to ensure they are progressing and produce quality work

- Manage and resolve requests/questions and independently answer and resolve calls from clients- Proactively communicate improvement potential within client accounts and be a strong partner in preparation for relationship nurturing Client Success calls

Hired team-leads and general members supporting the organization’s 72% YOY growth (QMIND became the largest student-run club at Queen's University in 2019), as well as coordinating on-boarding training for over 150 new and senior members. Furthermore, I managed and assessed 6 design team projects, collaborating with technical project managers to drive their strategy and promote high quality solutions that were presented at Canada’s largest undergraduate AI conference (CUCAI)

Led a small team with the focus of creating a functional and deployable computer vision model for Queen's University's on-campus grocery store. Was also responsible for creating and presenting educational material on machine learning concepts and frameworks.

Worked with Microsoft Azure to develop machine learning models. Also developed a program for physical access using Python that learned a user's patterns and determined if a request to open a door was high-risk or not.

Helped establish the foundation of BioConnect's "Trust AI Engine". This “Trust AI Engine” uses artificial intelligence to continuously authenticate who a person really is, for the purpose of reducing the chance of fraud. Contributed to the project by creating a machine learning model using TensorFlow that would be used to predict where a user is likely to login from next. I also did some simple electrical engineering work for a smaller side project.