Top AI Jobs in Toronto

Own the end-to-end improvement loop for Elastic’s Context Engine, including agent behavior, evaluation, telemetry, retrieval, memory, and safe production rollouts. Build production services in TypeScript or Python, design golden datasets and quality gates, analyze traces and customer feedback, and improve agentic systems through experimentation. Collaborate with data scientists, backend engineers, product, and UX while mentoring engineers and shaping technical strategy.

Generate qualified pipeline for Docebo’s North American mid-market team by identifying target stakeholders, crafting messaging, conducting outbound calls, qualifying prospects, handling inbound inquiries, and scheduling opportunities. The role requires strong communication, active listening, organization, self-motivation, creativity, and a results-oriented approach to sales development within a hybrid work environment.

Supports institutional client account management through market and portfolio analysis, performance attribution, customized reporting, presentations, and client inquiries. Builds dashboards and reporting resources, identifies workflow improvements, and helps implement AI-enabled tools, automation, and business intelligence solutions. Coordinates cross-functional initiatives, documents processes, supports change management, and trains users on new technologies. Requires financial markets knowledge, coding ability, strong analytical skills, and effective stakeholder communication.

Lead product strategy, portfolio execution, and AI-first transformation for Colliers’ proprietary commercial technology platforms. Oversee multiple Product Management teams, establish roadmaps and FED governance, partner with Data, AI, Engineering, and global business leaders, and deliver enterprise B2B products for sales and services professionals. Drive adoption, product telemetry, KPIs, ROI measurement, and AI-enabled workflows using cloud and analytics technologies.

Transactional attorney supporting M&A and Private Equity practices by identifying, evaluating, and implementing AI-enabled tools, document automation, prompt libraries, and knowledge workflows. The role enhances drafting resources, precedents, and knowledge infrastructure; analyzes market practice and legal materials; trains attorneys and staff; and translates legal judgment into scalable technology solutions. Requires at least four years of M&A or Private Equity experience, legal admission, strong communication skills, and interest or experience in workflow design, technology building, or process improvement.

Develop and maintain Selenium and Java UI automation frameworks; design functional, regression, and end-to-end tests; integrate test suites with CI/CD pipelines; apply GenAI tools to test creation, debugging, defect analysis, and optimization; and collaborate with development, QA, and business teams in Agile environments.

Develop computer vision and vision-language models for image and video understanding in restaurant environments. Build datasets, training strategies, evaluations, and benchmarks; diagnose model failures; and deploy efficient, reliable inference pipelines. The role combines research and engineering across scene understanding, object tracking, activity recognition, temporal reasoning, visual grounding, and multimodal models, while partnering with product and infrastructure teams to bring research into production.

Build and deploy internal AI tooling, agents, integrations, and workflows that improve productivity across engineering, research, and business teams. Evaluate emerging AI tools and models, develop observability and responsible-use guardrails, and partner with stakeholders to prototype and scale solutions. Drive adoption through documentation, enablement, and hands-on support while integrating AI into autonomy, simulation, ML training, and business workflows.

As an AI Forward Deployed Engineer, you'll design AI workflows, act as a customer technical bridge, and optimize deployment performance. You'll thrive in a fast-paced, early-stage environment, shaping tools and documentation while ensuring system reliability.

Leads AI and Generative AI engagements from discovery through production, serving as the client and technical delivery lead. Combines project management with hands-on architecture and development of LLM applications, RAG pipelines, AI agents, APIs, and cloud-based services. Coordinates cross-functional teams, manages risks and delivery milestones, translates business needs into technical solutions, and oversees evaluation, monitoring, deployment, and production readiness.

Owns a Canadian enterprise and public-sector territory, driving new business, account expansion, renewals, forecasting, and revenue growth. Advises CISOs, CIOs, and board executives on cybersecurity solutions, leads matrixed teams through workshops and pilots, and partners with channel organizations and system integrators. The role requires consultative enterprise selling, complex deal negotiation, strategic account planning, pipeline management, and strong cybersecurity and cloud fluency.

Lead engineering execution and technical direction while remaining approximately 75% hands-on. Responsibilities include developing LLM- and AI-powered products, coding, code review, debugging, platform performance, sprint planning, cross-functional coordination, technical mentorship, recruiting, and supporting engineers’ growth. The role partners closely with founders and product teams and offers a path toward Engineering Manager responsibilities.

Leads enterprise AI enablement, adoption, platform stewardship, and operational services across EQB. Establishes AI platform strategy, onboarding, access, support, reliability, observability, lifecycle management, vendor coordination, FinOps, and responsible scaling practices. Drives learning pathways, change management, communities of practice, executive engagement, and measurable adoption outcomes while coordinating engineering, architecture, governance, cybersecurity, risk, privacy, legal, infrastructure, and business stakeholders.

Conduct research in Physical AI, Embodied AI, and Spatial AI, developing robotic foundation models, world models, multimodal systems, planning, reasoning, imitation learning, reinforcement learning, and control methods. Translate research into production-ready code, run experiments in simulation and on real robots, collect and analyze data, collaborate with infrastructure and robotics teams, and contribute to patents and publications at leading AI and robotics venues.

Own the roadmap, quality bar, evaluation frameworks, and product outcomes for Caseware’s AI agents, agent builder, eval builder, and agentic memory. Partner with applied scientists, engineers, auditors, and accounting firms to validate outputs, define acceptance criteria, measure product health, and determine what ships. Translate practitioner workflows and failure modes into actionable requirements while monitoring AI advancements and coordinating delivery across technical teams.

Own and scale AI-powered agentic products for home care organizations, including voice staffing, EVV support, and caregiver-facing experiences. Define roadmaps, success metrics, reliability standards, experiments, and release priorities. Partner with Engineering, Data, Design, Customer Success, Marketing, and users to improve adoption, engagement, ROI, and business outcomes. The role requires taking AI products from 0-to-1 into reliable production experiences while supporting go-to-market efforts.

Own the strategy, development, optimization, and documentation of GoHighLevel-based outbound, nurture, automation, AI agent, and collateral systems. Build workflows, integrations, funnels, campaigns, voice agents, and reusable client assets across GoHighLevel, n8n, HubSpot, and related platforms. Develop messaging, analyze performance, troubleshoot systems, maintain quality assurance processes, train internal teams, and support client strategy while continuously evaluating emerging AI and RevOps technologies.

Own paid acquisition across Google, Bing, Meta, and YouTube, scaling campaigns from creative production through launch, optimization, and attribution. Produce high-volume ad assets using AI tools, manage full-funnel campaigns, improve campaign processes, automate repetitive work, and analyze CAC, ROAS, payback, and product activation data. The role requires hands-on Google Ads expertise, creative production skills, subscription funnel experience, and strong ownership in a remote startup environment.

Lead management consulting engagements and transformation workstreams from problem definition through implementation and adoption. Advise senior client stakeholders, conduct strategic and operational analysis, design operating models and process improvements, and translate AI opportunities into practical roadmaps. Manage delivery, risks, stakeholders, and project teams while coaching consultants. Support proposals, pitches, account growth, thought leadership, and new offerings, helping clients build sustainable AI-enabled capabilities and ways of working.

Leads Absorb’s product management organization, translating company strategy into product roadmaps, portfolio investments, and measurable outcomes. Oversees PM team development, operating models, governance, customer advocacy, capacity planning, and cross-functional delivery across product pods. Drives practical AI adoption in product workflows, establishes measurable adoption goals and guardrails, and strengthens strategic product management capabilities. The role requires extensive B2B SaaS product leadership and experience scaling high-performing PM teams.

Build scalable end-to-end Generative AI applications using Java, Python, microservices, Angular, and React. Develop backend APIs, distributed workflows, ML model integrations, responsive enterprise interfaces, and cloud-native deployments. Own testing, CI/CD, containerization, performance, security, and fault tolerance. Collaborate with UX, product, ML, and cross-functional teams while mentoring junior developers and driving engineering best practices.

Conduct research on AI agents, LLMs, VLMs, code generation, and multimodal AI. Develop GUI, coding, web, mobile, and computer-use agents; create training pipelines, datasets, benchmarks, and evaluation frameworks; and investigate supervised fine-tuning, reinforcement learning, tool use, and function calling. Analyze experiments, publish findings, collaborate with engineering and product teams, and translate research prototypes into practical technologies.

Build and optimize production-grade agentic AI systems for marketing and enterprise customer experience use cases. Responsibilities include agent orchestration, tool use, RAG, embeddings, guardrails, LLM evaluation, observability, performance optimization, and scalable Python services deployed on AWS. The role partners across product and engineering teams and requires hands-on experience with LLM agents, marketing data platforms, retrieval systems, and AI evaluation.

Design and build scalable Python backend applications and RESTful APIs, develop and optimize prompts and Generative AI solutions (LLMs), integrate AI capabilities into enterprise systems, collaborate with architects and data specialists, and contribute to code reviews and continuous improvement.

Develop AI/ML strategy and production software for Smile Digital Health’s healthcare data platform. Design architectures and implement semantic matching, RAG, document parsing, agentic systems, knowledge graphs, and evaluation workflows. Write clean, tested, documented code, integrate external components, conduct reviews, collaborate with clients and product teams, contribute to technical strategy, and mentor developers in an Agile environment.