Top AI Jobs in Toronto

Lead Crossfoot as founding CEO: define strategy, run customer development and pilot programs with CPA firms, partner with product/engineering to ship V1, raise seed funding, recruit and build the founding team, and drive go-to-market and pricing for an AI-native accounting agent platform.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

As a Social Media Intern at Inception, you will manage social content across platforms, engage with AI discussions, participate in product launches, and create engaging video content. Aimed at students with a passion for AI and strong writing skills, the role offers direct access to the founding team and the potential for full-time conversion.

As a Chatdesk Expert, provide customer support for brands through social media and email. Set your own schedule and work remotely.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.

Lead identification, prioritization, and implementation of AI-driven use cases and automation across global programs. Drive POCs, design future-state workflows, gather requirements, build governance, create AI-enabled dashboards and playbooks, partner with IT/vendors, and train teams to increase adoption and operational efficiency.

Design, prototype, and ship production AI/ML features that analyze observability data to detect, triage, and resolve incidents. Rapidly iterate on LLM- and agent-powered workflows, collaborate cross-functionally, integrate AI with internal tools and alerting systems, and ensure solutions are scalable, maintainable, and aligned with user workflows.

Design and implement production-grade agentic AI systems and platform components that generate enterprise agents from messy source material. Architect agent workflows (reasoning, tool use, retrieval, guardrails), build evaluation and RAG/embedding systems, diagnose performance issues, and collaborate with product and engineering teams to deliver scalable, reliable AI agent features in AWS.

Lead and grow a Vincent AI software engineering team: collaborate with product and design, design technical solutions, perform code reviews and hands-on development, hire and coach engineers, drive roadmaps, and improve processes with an AI focus.

Lead design, build, and automation of AWS infrastructure using Terraform; create and improve CI/CD pipelines; support a multi-tenant SaaS platform for reliability and security; integrate AI tooling, AI agents, and MCP servers into DevOps workflows to boost delivery speed and reduce toil; establish monitoring, access control, and operational best practices; collaborate with cross-functional teams and communicate with stakeholders.

Design, build, and productionize LLM-powered applications and agentic AI systems. Develop data and inference pipelines, deploy and monitor models, define evaluation frameworks, optimize performance/cost, and enforce governance, safety, and observability to deliver scalable AI-driven customer experience solutions.

Lead multiple sales clusters for an AI advertising platform, develop sales strategies, coach and onboard sales teams, analyze performance via dashboards, manage client relationships, present business reviews, ensure compliance, and drive growth through strategic frameworks and advanced analytics.

Lead the design and development of AI services, managing technical teams to create enterprise-wide Generative AI platforms and solutions.

Design, develop, and test software for software analytics, source-code mining, software analysis, reverse engineering, and migration. Rapidly prototype research ideas into code transformations and prototypes, collaborate with product teams to integrate solutions into Huawei products, and apply computer vision and machine learning expertise to advance applied 3D AI research.

The role involves researching and developing advanced networking technologies for AI infrastructure and cloud data systems at Huawei, focusing on performance and innovation.

The Senior Developer, Enterprise AI will lead the design and implementation of AI-enabled workflows, collaborating with cross-functional teams to develop secure and scalable solutions while mentoring junior developers.

The Senior AI Engineer will design and integrate AI features into backend systems, optimize models, and collaborate with teams for deployment and architecture best practices.

Lead strategy and research for Generative AI and Graph ML, drive end-to-end ML system design and production deployments, mentor scientists, align ML innovation with product goals, and represent the company externally.

Lead AI engineering strategy and team to productize generative AI and autonomous systems. Drive end-to-end delivery from research to enterprise production, set architecture and reliability standards for LLMs, RAG, and multi-agent systems, and partner cross-functionally to measure business impact.