Top AI Jobs in Toronto

Build and maintain the Python-based backend engine for GitLab Duo Chat, including agentic LangGraph flows, the Flow Registry, and Duo Workflow Service. Integrate chat capabilities with GitLab’s Rails monolith and GraphQL API, develop secure and tested high-scale features, optimize performance, review code, address technical debt, and collaborate cross-functionally. Participate in weekday, weekend, and occasional nighttime Tier 2 or Tier 3 on-call rotations.

Own the function’s AI transformation strategy, prioritize high-impact opportunities, map workflows, and drive measurable adoption. Build and manage AI agents using no-code and low-code tools, configure skills and MCP connections, evaluate agent performance, and iterate solutions. Lead change management, champion networks, cross-functional collaboration, intake processes, and alignment with Enterprise AI and executive stakeholders.

Build and deploy agentic and generative AI systems that automate risk and compliance investigations. Own full-stack ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based modeling across transaction, graph, text, and profile data. Collaborate with product, engineering, platform, and operations teams while leading strategic roadmaps and delivering scalable production systems.

Build and deploy agentic and generative AI copilot and autopilot systems for risk and compliance automation. Own end-to-end ML systems, including data integrations, prompt tuning, orchestration, evaluation, productionization, monitoring, and transformer-based model development. Collaborate with product, engineering, platform, and operations teams to improve fraud detection and analyst productivity. Drive strategic roadmaps and cross-functional programs with significant business impact.

Design and deliver enterprise-scale AI platform capabilities: architect cloud-native, scalable AI systems, build backend services and reusable platform components, define standards for deployment, observability, security and resilience, lead architecture and governance reviews, contribute hands-on development, and mentor teams to drive enterprise AI adoption.

Designs, builds, deploys, and supports AI-powered tools and automated workflows for Finance operations. Develops data pipelines, reporting applications, workflow automation, interactive applications, and AI-assisted analysis tools. Collaborates with Finance and technical stakeholders to improve processes, data quality, and decision-making. Supports development standards, CI/CD, AI governance, data compliance, troubleshooting, and ongoing enhancements.

Provides insurance product expertise and leadership across underwriting, product design, policy administration systems, and change initiatives. Analyzes portfolio issues, develops underwriting and risk-selection solutions, coordinates requirements, identifies improvement opportunities, and supports AI-driven underwriting experience enhancements. The role requires collaboration with stakeholders, product prioritization, solution feasibility assessment, risk mitigation, and coaching colleagues in an agile environment.

Lead global sales enablement programs that drive measurable revenue by diagnosing performance gaps, creating role-based training and playbooks, aligning cross-functionally, and optimizing adoption through analytics and manager-led reinforcement.

Own end-to-end product experiences across web and native mobile: set design vision, run user research, rapidly prototype (AI-enabled), write production frontend code, evolve design systems, mentor designers, and drive measurable product outcomes.

The Senior Applied Scientist will lead research projects in AI/ML for various legal and taxation solutions, focusing on developing scalable AI capabilities while mentoring junior team members.

Design, develop, and maintain scalable .NET and React applications and secure RESTful APIs. Implement authentication/authorization (JWT, OAuth2), containerize with Docker, contribute to CI/CD, code reviews, and documentation, and responsibly use AI-assisted development tools to improve productivity and quality.

Build and ship production-grade agentic AI workflows across Acquia’s digital experience platform. Design stateful multi-agent systems using LangGraph, Temporal, and Pydantic; own LangFuse observability, evaluation, and benchmarking; establish standards for RAG, prompting, context optimization, and tool calling; partner on secure, reliable enterprise architectures; evaluate AI tooling; mentor engineers; and support customer architecture and roadmap discussions.

Lead scientific and strategic AI efforts for Vaccines Medical: define AI vision and roadmap, govern responsible AI standards, prioritize and deliver validated AI-enabled solutions, partner cross-functionally, oversee deployment and adoption, manage budget and vendors, and ensure regulatory, ethical, and scientific compliance across global medical affairs.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Lead AI assurance and analytics efforts: design and assess ML/deep learning solutions, conduct large-scale analyses, develop predictive models, advise leaders, collaborate with product teams, manage and coach a high-performing team, ensure AI trust, bias, ethics and risk-aligned decision-making across the enterprise.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Lead technical vision and architecture for AI-powered GTM systems, defining reference architectures, patterns, and governance for low-code and custom agentic solutions. Architect and prototype LLM orchestration, multi-system integrations, RAG pipelines, and event-driven data flows across Salesforce, NetSuite, Marketo, and cloud infrastructure while partnering with GTM leaders to deliver production-grade, auditable, and scalable automation.

Lead end-to-end UX across Babylist web and mobile: run user research, build rapid interactive prototypes, write production front-end code, evolve the design system, instrument outcomes, and champion AI-native design workflows to create intuitive, delightful experiences for families.

Lead high-impact strategy advisory engagements for SMEs and mid-market clients, oversee multiple concurrent mandates end-to-end, advise on enterprise strategy, M&A and post-merger integration, support consulting business development, and contribute to methodology and thought leadership.

Own the end-to-end creation and optimization of performance-driven advertising across TikTok, Meta, YouTube, CTV, and emerging channels. Develop concepts, scripts, hooks, creative frameworks, briefs, and edited video assets while maintaining strong visual and brand quality. Use performance data, platform trends, AI tools, and media insights to improve creative effectiveness. Direct agency and production partners, collaborate with growth and analytics teams, and scale Jerry’s creative output.

Lead the roadmap, development, and rollout of Jerry.ai’s customer-facing Agentic AI platform. Partner with engineering and OpenAI to design prompt strategies, evaluation frameworks, guardrails, voice models, and workflow automation. Translate technical architecture into organizational standards, improve answer quality and automation through experimentation, and balance latency, cost, and accuracy. The role owns the consolidation and advancement of AI capabilities across chatbots, validation, back-office automation, voicebots, computer-use agents, and consumer AI applications.

Build and maintain backend AI capabilities for GitLab Duo Chat: design flow components and agentic flows in Python/LangGraph, integrate LLMs and multi-agent orchestration, implement and maintain APIs in the Rails monolith, improve observability and reliability, and participate in on-call rotations and cross-functional collaboration to deliver safe, scalable AI chat features.

Own and improve the AI Social generative media pipeline: build and ship LLM-driven prompts/agent loops, choose and compose media (image, video, voice, music), collaborate with product/design/content, and deliver polished, production-quality social assets.

Support customer deployments and adoption of Regology by serving as a technical subject matter expert and project manager. Lead enterprise integrations, API discussions, AI-related technical conversations, training, troubleshooting, and requirements translation across customers, product, engineering, and sales teams. Coordinate implementation activities, resolve integration issues, and provide technical support during customer and sales engagements.