Top Tech Jobs & Startup Jobs in Toronto

Leads client-facing data science and AI consulting engagements, developing predictive models, generative AI and agentic systems, cloud analytics workflows, and executive dashboards. Designs RAG pipelines, LLM applications, machine learning models, and scalable data architectures while facilitating client workshops, documenting solutions, supporting presales, and mentoring junior team members.

Lead the architecture and hands-on delivery of end-to-end Azure data platforms, including ingestion, transformation, lakehouse modeling, analytics, APIs, and activation. Build batch and streaming pipelines with Microsoft Fabric, Azure Data Factory, Databricks, Python, PySpark, and SQL. Implement governance, security, CI/CD, MCP and agentic AI integrations, while troubleshooting production systems. Mentor engineers, advise client stakeholders, contribute to presales, and establish reusable engineering standards.

Leads engineers and technical leads in delivering AI-powered customer experience and contact center products. Responsibilities include solution architecture, technical design reviews, implementation planning, customer deployments, cross-functional coordination, risk management, operational readiness, and evaluation of emerging AI and CCaaS technologies. The role develops architecture diagrams, oversees complex software implementations, and guides integrations across cloud, AI, and contact center platforms.

Senior SDET responsible for automation-first quality engineering for AI-driven CX platform. Build and maintain fast, parallelized regression suites, load/stress tests, CI-integrated tests, API/contract tests, and synthetic traffic generation. Rapidly detect, isolate, and report issues; collaborate with devs to ensure weekly deploy quality for real-time, event-driven services.

Lead-platform principal engineer who codes, debugs, and sets reference implementations across AI-powered CX systems. Own platform architecture decisions, unblock squads by shipping production code, mentor engineers, and build high-capacity, event-driven distributed systems integrating messaging, multiple DB types, multi-cloud, and advanced AI (LLMs, RAG, agents).