Top AI Jobs in Toronto

Develops communications strategy and thought leadership for cybersecurity, identity, access management, and AI topics. Responsibilities include media relations, executive communications, contributed content, event and speaking strategies, rapid response, narrative development, journalist engagement, and communications measurement. The role translates complex technical concepts into credible messaging for developer, business, and security audiences while collaborating with marketing, product, engineering, security, legal, sales, executives, and agencies.

Own Spellbook’s entire product function, including product vision, portfolio strategy, roadmap prioritization, execution, launches, customer insight, analytics, and cross-functional alignment. Lead and grow a team of Product Managers while partnering with engineering, design, marketing, sales, customer success, and the CEO. Drive AI-powered B2B SaaS product development and contribute to company strategy, investor narratives, and fundraising efforts.

Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.

Build and operate customer-facing SaaS applications using Java, Spring, React, and TypeScript. Own complex features from design through production support, develop APIs and distributed systems, improve frontend experiences, apply AI-assisted coding tools, modernize legacy software, strengthen CI/CD and observability, and mentor engineers through technical leadership and code reviews.

Develop and deploy computer vision and multimodal AI models for e-commerce applications, including search, recommendations, content generation, and video understanding. Build training, inference, evaluation, and agentic AI pipelines; conduct rigorous experimentation and error analysis; and productionize foundation-model-based systems. Collaborate with product, engineering, design, and research teams to translate business needs into scalable machine learning solutions.

Build and deploy secure, reusable LLM infrastructure across its lifecycle; lead emerging-technology research and proof-of-concepts; enable engineering teams with AI tooling and guidance; advise product teams on technical decisions; and improve code quality, performance, processes, and long-term technical strategy.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Designs, automates, and operates self-hosted Linux and Kubernetes infrastructure across global bare-metal environments. Responsibilities include maintaining high availability, managing control planes and container platforms, troubleshooting system-level incidents, conducting root-cause analysis, building automation and self-service tools, improving observability, and supporting production systems through on-call rotation. The role also collaborates with distributed engineering teams on infrastructure standardization and may support AI/ML workloads.

Engineering Manager, Applied AI leads and coaches engineers while remaining hands-on on client engagements. Responsibilities include reviewing architecture, agent, prompt, and evaluation designs; resolving technical and client challenges; managing staffing and delivery; hiring and onboarding engineers; and improving engineering practices. The role requires strong software engineering experience, Python expertise, client-facing delivery experience, and familiarity with agents, evaluations, multi-agent systems, and AI coding tools.

Develop and deploy multimodal AI and computer vision models for eBay’s search, recommendations, content generation, video, and live-streaming applications. Responsibilities include designing scalable training and inference pipelines, fine-tuning visual-language models, building agentic AI workflows, evaluating and monitoring production systems, shaping technical strategy, partnering with cross-functional leaders, and mentoring researchers.

Develop and deploy computer vision and multimodal machine learning models for search, recommendations, video, and live streaming. Own applied research projects end to end, including data preparation, experimentation, evaluation, pipeline design, and production deployment. Build visual-language and agentic AI systems, conduct rigorous model analysis, and collaborate with product, engineering, design, and research teams to deliver scalable user and seller experiences.

Design, build, and operate production AI and automation solutions for clients. Lead discovery, solution design, proofs of concept, integrations, document processing, knowledge assistants, security controls, and ongoing optimization. Productize successful client work into packaged services, reusable accelerators, reference architectures, and repeatable delivery methods. Advise technical and executive stakeholders while helping shape the company’s AI offerings.

Leads AI, AEO/GEO, and growth product strategy for Uberall, including roadmap development, product innovation, product-led growth, and customer retention. Manages and mentors global product managers while collaborating with engineering, design, marketing, sales, customer success, and senior leadership. Uses market trends, customer data, competitive analysis, and product metrics to guide decisions and optimize initiatives. Requires deep AI and SaaS expertise, strong growth strategy experience, and a proven record of launching and scaling successful products.

Design and build agent-based and multi-agent AI systems that use tools, plan tasks, evaluate outcomes, learn from feedback, and recover from failures. The intern will develop agent workflows, memory and delegation systems, evaluation frameworks, human-review processes, and long-running autonomous systems while applying current AI research.

Own the architecture and technical strategy for Square’s go-to-market technology stack. Build and operate production AI agents, automated workflows, and integrations that improve sales productivity. Lead complex technical initiatives across teams, establish reliable and secure AI evaluation practices, make build-versus-buy decisions, and partner with Sales, Product, Data, and Engineering leaders. Mentor engineers, guide design and implementation, and use data and feedback to improve system adoption and business impact.

Leads application development engineering and AI integration initiatives. Designs scalable distributed systems and microservices, drives adoption of AI-powered development tools, and guides development of agentic architectures, RAG systems, multi-agent workflows, and A2A communication. Partners with product, design, and business stakeholders while providing technical leadership, promoting agile practices, and delivering resilient software products.

Lead Voyager, Relay’s applied AI and innovation engineering team. Own shared LLM infrastructure reliability, security, deployment, and monitoring; guide production agentic systems; lead emerging-technology research and proofs of concept; enable teams with AI tooling and patterns; oversee delivery and engineering processes; and hire, coach, and develop senior and staff engineers.

Own the architecture and technical strategy for Square’s go-to-market technology stack. Build and operate production AI agents, automated workflows, and scalable integrations that improve sales productivity. Lead complex technical initiatives across teams, establish AI reliability and security guardrails, define evaluations and success metrics, and guide build-versus-buy decisions. Remain hands-on across prototyping, implementation, testing, deployment, and operations while mentoring engineers and influencing senior business and technical stakeholders.

Leads AI strategy, solution architecture, prototyping, automation, innovation, governance, adoption, and measurement across AdFarm and selected client work. Translates business challenges into AI solutions, prioritizes opportunities, evaluates build-versus-buy decisions, leads pilots, partners cross-functionally, and communicates results and investment needs to senior leaders. Requires hands-on AI application design, technical fluency, change leadership, stakeholder influence, and agency or professional-services experience.

Lead and grow a solution engineering team for AI-powered Dynamics 365 business solutions. Own technical win strategy, coach demos and solution design, partner with sales to convert pipeline, enable value assessments, manage proposals, and align with partners and Customer Success to achieve revenue and deployment outcomes.

Principal Software Engineer leading architecture and implementation of resilient, low-latency distributed systems for the RunMyJobs platform. Responsibilities include technical strategy, full-stack development, AI-assisted software development, CI/CD and observability, code and design reviews, quality improvement, troubleshooting, and mentoring. The role requires expertise in Java, microservices, cloud platforms, containers, frontend technologies, databases, automated testing, and AI developer tools, with broad technical ownership but no direct people management.

Build and deliver production AI systems across machine learning, generative AI, and agentic workflows. Design scalable ML and data pipelines, integrate heterogeneous data, evaluate emerging AI frameworks, and deploy secure cloud-native solutions. Collaborate with data science, product, security operations, and threat research teams to deliver customer value. Write and review code, troubleshoot production issues, measure AI quality, document technical decisions, and mentor engineers.

Build and own customer-facing product features end to end, from customer discovery and prototyping through production deployment and validation. Develop across Rails APIs, React and TypeScript frontends, AI agents, realtime voice, video, search, and analytics. Work autonomously with founders and product teammates, use AI coding tools daily, maintain production systems, make UX decisions, and take accountability for product outcomes.

Design and implement advanced Generative AI models, optimize performance for LLMs, and collaborate with cross-functional teams to innovate AI solutions within the automotive sector.

Triages and resolves product bugs by interpreting user feedback, working in the codebase, submitting and validating fixes, and monitoring product quality. Tests edge cases, documents recurring issues, communicates status clearly, and uses Claude Code and other AI tools to accelerate work while applying strong product judgment. The role is fully remote for US or Canada-based independent contractors, with potential for conversion to full-time employment.