Top AI Jobs in Toronto

Lead and support product strategy and roadmaps for digital platforms, drive product launches, market and competitor analysis, and collaborate with sales, implementation, global product, technology and operations teams to deliver client-focused digital solutions and meet financial and acquisition targets. Ensure compliance, risk awareness, and continuous product improvement using data and client feedback.

Lead multidisciplinary engineering teams delivering complex projects for nuclear clients. Provide technical leadership, client escalation management, proposal and design review for digital systems, collaborate with sales and executives, and drive departmental strategy while ensuring high safety and quality standards.

Identify business challenges and translate them into AI initiatives; architect AI solutions using appropriate models, frameworks, and infrastructure; guide data science and engineering teams through proof-of-concept development and deployment; mitigate bias and model drift through monitoring; and communicate an AI vision aligned with business goals.

The VP of Engineering will own engineering strategy, architecture, scaling, hiring, performance management, and people development. This hands-on leader will write and review code, establish technical direction across two pods, develop engineers into technical leads, represent engineering to executives, and partner cross-functionally to prioritize and deliver critical work. Experience in healthcare, HIPAA, or SOC 2 environments is preferred.

Drive new business and revenue growth for commercial insurance through pipeline development, consultative selling, client relationship management, and quota attainment. Use CRM, analytics, predictive insights, and AI tools to prioritize opportunities, manage sales cadences, forecast revenue, and identify upsell opportunities. Develop strategic growth plans, conduct market and competitive research, collaborate with service and marketing teams, and serve as a trusted advisor to clients.

Leads 1Password’s analytics engineering function, owning data architecture, roadmap, modeling, semantic layers, BI tooling, pipelines, governance, testing, documentation, and data quality. Manages and develops analytics engineers, establishes technical standards, reviews complex dbt and SQL work, optimizes warehouse performance, and partners with senior leaders across Finance, Marketing, Product, Analytics, and Data Engineering. Builds trusted data foundations supporting company-wide decisions, AI initiatives, and generative BI.

Develops, calibrates, validates, and maintains credit risk models, including PD, LGD, and EAD models, for lending, collections, loss forecasting, capital planning, and stress testing. Analyzes large datasets, evaluates model performance, documents model changes, supports systems testing, and communicates statistical insights to stakeholders and management. Collaborates across the credit union to improve risk-return strategies and reporting.

Lead ShipMonk’s global talent acquisition function across high-volume warehouse hiring, corporate and technology recruiting, and senior searches. Build scalable, data-driven recruiting systems, define hiring metrics, coach recruiters, train hiring managers, shape the talent brand, and introduce AI-enabled recruiting tools. Initially serve as a hands-on player-coach before transitioning to broader team leadership. Travel 25–30% across fulfillment sites and corporate offices.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

Lead month‑end and quarter‑end consolidation and reporting across regions and currencies. Manage intercompany, equity, and treasury transactions; deliver fluctuation analysis and commentary; coordinate with Tax, GL, FP&A and Financial Operations; drive process improvements and leverage technologies to streamline reporting and meet tight deadlines.

Lead Sierra’s largest and most complex enterprise sales opportunities across business units and geographies. Build trusted C-suite relationships, structure multi-million-dollar deals, manage risk and pricing, engage customers alongside founders, and shape strategic account and sales strategy. Use AI tools throughout the sales cycle for research, outreach, forecasting, summarization, and deal execution. The role requires executive-level communication, precision, and experience closing complex six- and seven-figure ACV deals.

Build LanceDB’s revenue marketing function and enterprise demand engine from the ground up. Own account-based marketing strategy, segmentation, campaigns, content, account planning, martech implementation, pipeline reporting, and partner co-marketing. Identify high-intent accounts through open-source and product-usage signals, create tailored omnichannel programs, and collaborate closely with founders, Sales, RevOps, and Partners to source and influence enterprise pipeline.

The Director, Fundamental Credit Risk conducts credit risk assessments for debt investments, partners with investment teams, and enhances credit monitoring practices using analytics and AI.

Own the full sales engagement cycle for AI-powered business process solutions, including opportunity identification, account planning, executive relationship development, solution demonstrations, value propositions, pipeline creation, contract renewals, and customer success planning. Partner with account executives, engineers, marketing teams, and channel partners to drive adoption of Dynamics 365, Power Platform, and Copilot, achieve revenue targets, and advise customers on business transformation.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Serve as the primary technical advisor for SMB sales opportunities, partnering with Account Executives throughout sales cycles. Lead technical discovery, product demonstrations, proof-of-value engagements, competitive evaluations, security questionnaires, RFPs, and technical documentation. Advise IT, security, developer, DevOps, and executive stakeholders on identity, endpoint, SaaS, secrets, cloud, and AI security solutions. Collaborate cross-functionally to improve demos, playbooks, enablement, and customer education.

Manage the end-to-end sales process for existing financial services clients, focusing on upselling hedge funds, asset managers, investment banks, and sell-side research teams. Responsibilities include prospecting, pipeline development, product demonstrations, trials, relationship management, forecasting, closing sales, and meeting targets. The role partners with marketing and product teams, gathers client feedback, and requires regular client travel.

Leads global strategic sourcing and procurement for digital technology and Food & Nutrition categories. Manages $125M+ in spend, SaaS and professional services suppliers, sourcing strategies, RFPs, contracts, supplier governance, performance, risk, and cost optimization. Partners with senior stakeholders, Legal, Infosec, sourcing teams, and suppliers to support digital transformation, standardization, automation, and commercial objectives.

Build and enhance AI and data solutions for insurance by collaborating with data architects, scientists, and engineers. Use AI-first tools and agents, design prompts, prototype generative AI, review AI-generated code for security and quality, track production trends, document patterns, participate in code reviews, and assist senior staff to scale AI capabilities across the platform.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Design, build, and operate production AI systems and marketing data infrastructure. Develop retrieval pipelines, agent orchestration, CDP integrations, ETL/ELT pipelines, and analytics. Automate workflows with AI, ensure data quality and reliability, partner with stakeholders, ship Python and SQL code, mentor engineers, and drive requirements to production.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, including LLM inference infrastructure, RAG, AI agents, and evaluation/observability. Design and run experiments (A/B tests), optimize systems for production performance and reliability, and iterate rapidly with product and design partners.

Lead and grow an engineering team for a large-scale SaaS product, providing hands-on technical leadership, code reviews, and architecture guidance. Collaborate with Product and Design to set roadmaps, contribute to implementation, hire and coach engineers, and support career development and team performance. Foster a feedback culture and adapt processes and technology, especially around AI.

Lead development and deployment of production-grade generative AI applications for sales enablement. Build copilots, automated outreach, and voice/chat interfaces; work across model experimentation, app development, and infrastructure; partner with revenue ops, product, and engineering to scale AI features that improve efficiency and personalization across the sales funnel.