- Independently leads and holds responsibility for multifaceted programs made up of multiple projects and processes; develops and reviews business cases for change and improvement
- Design and build end-to-end AI systems integrating ML models, LLMs, APIs, and enterprise data
- Translate business requirements into scalable system architectures and solution designs
- Develop backend services and API-driven architectures to operationalize intelligent systems
- Implement data and model pipelines integrating structured and unstructured data sources
- Work closely with Data Scientists and ML Engineers to integrate model outputs into production systems and decision workflows
- Apply agent-based workflows and multi-step orchestration to enable complex system behavior
- Ensure systems are production-ready—scalable, reliable, secure, and performant
- Continuously improve system performance through testing, monitoring, and iterative refinement
- Work closely with business, product, Data Science,



and engineering teams to co-create solutions and align on outcomes
- Translate ambiguous problems into structured requirements and actionable system designs
- Engage stakeholders regularly to refine solutions and drive adoption
- Collaborate across teams to ensure integration with existing systems and enterprise standards
- Maintain high-quality documentation and enable knowledge transfer and continuity
- Take ownership of delivery by managing enhancements, releases, and system evolution
- Stay current with industry trends and contribute to continuous improvement of team capabilities

Bachelor’s degree in Computer Science, Machine Learning, Data Science, or a related field5+ years of experience in software engineering, AI/ML engineering, or related roles, with demonstrated experience in building and integrating production-grade systems

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📌 AI/Machine Learning Engineer (Toronto)
🏢 Equinix
📍 Toronto