• Act as the bridge between data infrastructure and customer-facing AI products. • Specialize in building low-latency API layers, production-grade RAG systems, complex ingestion pipelines, and Human-in-the-Loop workflows. • Work alongside Data Engineers to turn raw data lakes into live AI features.

• Design and build the foundational AI layers for broader engineering organization • Implement prompt frameworks and enforce deterministic structured outputs • Deploy production-grade Human-in-the-Loop state automations • Turn raw context into reliable, zero-hallucination agent-based actions

Role Description This course emphasizes the educator’s evolving role as observer and co-learner, with a focus on pedagogical documentation in K–6 settings. Through experiential and collaborative analysis of classroom practice, current research, and Ministry policy, teacher candidates will investigate how documentation and assessment can be used to design, interpret, and extend inquiry-based learning. The course foregrounds the educator’s role in making learning visible - to students, families, and colleagues - and in connecting inquiry to intentional, skills-based instruction. Teacher candidates will consider how equitable and culturally responsive practices are sustained when documentation and assessment are used as tools for reflection, collaboration, and responsive planning. Successful candidate will work with the course lead and/or team in order to provide consistency across sections. Qualifications - Master’s degree in Education - Bachelor of Education and/or K – 10 Teaching Certification - Experience in K-6 settings - Doctoral degree in Education - Post-secondary experience with focus on assessment and evaluation and/or inquiry-based research practices Requirements - Position Title: EU499 P VS: Learning Through Observation (Fall 2026) - Term: Fall 2026 - Dates of Term: September 8 - December 18th, 2026 - Mode of Delivery: Virtual Synchronous - Type of Instruction: Online - Days/Times: Thursday 5:30 – 6:50pm - Hours per week/Hours Total: 1.5/12 (0.25 credit) - Anticipated Class Size: 40 - Additional Course Requirements: None - Salary: $5106.20 - Application Deadline: June 25, 2026 Benefits - Required for All Applicants: - CV - Teaching Dossier - Candidate Application Form (CAF) - Required for External Applicants: - Names and Contact Information for Referees - Evidence of Good Teaching (e.g., teaching philosophy; assessment practices; scholarship that informs your teaching; evaluations) - Verification of highest degree - Optional: - Cover Letter - Teaching Dossier - Sample Course Outline

• Lead highly complex data science and analytics projects in support of process improvement, defect reduction, and predictive analytics for manufacturing and business applications. • Demonstrated project management skills, serving as project lead guiding less experienced team members in multiple facets of project execution. • Independently develop data science models or algorithms using disciplined software development processes, making recommendations for developing new code or re-using existing code, implementing version control, and maintaining documentation of created applications. • Define and implement ingestion, data preparation, curation, and governance of large, multi-faceted data sets supporting analytics models and workflows. • Proactively assess current capabilities to identify areas for improvement proposing solutions that align with core strategy and operation. • Guide and produce information products, supporting visualization and data accessibility in a customer centric manner. • Evaluate and make recommendations regarding technical advances that improve productivity and quality, reduce flow times, and enhance operational surety. • Develop guidelines and standards for analytics and machine learning models, their deployment, and associated processes. • Provides technical guidance or business process expertise, technical leadership, coaching and mentoring to team members. • Expected to communicate and collaborate within the team and participate with the team’s interfaces to the rest of the organization. • Interface with other teams and design software units for the team’s products