Top AI Jobs in Toronto

Develop secure integrations enabling AI agents and applications to access exchange market data. Build backend services and APIs using Python, Java, or comparable technologies; implement authentication, authorization, identity management, licensing, entitlements, and usage controls. Apply market-data distribution expertise and AI integration patterns such as LLMs, agentic AI, and MCP while collaborating with financial institutions and technology stakeholders.

Develop AI-enabled solutions for market surveillance, including alert investigation, trading-pattern analysis, anomaly detection, evidence gathering, and exception handling. Apply Python, SQL, machine learning, and LLM technologies to order, trade, and market data. Collaborate with compliance, surveillance, and technology stakeholders to translate operational requirements into scalable analytical and workflow solutions supporting trading compliance and market-abuse detection across equities and derivatives.

Develop AI-powered document-processing solutions for corporate actions and asset servicing. Build Python, API, LLM, and Document AI capabilities to extract and validate information from corporate-action documents. Translate complex business rules into technical workflows, collaborate with financial-services stakeholders, and improve securities-processing accuracy, scalability, and efficiency.

Develops advanced fraud analytics and machine learning solutions using large structured and unstructured datasets. Builds predictive models, identifies patterns and trends, evaluates AI/ML feasibility, and provides data-driven recommendations to business leaders. Partners with product and analytics teams on planning and roadmaps, delivers technical and analytical support, and applies risk management principles to protect the bank.

Leads TMX’s enterprise Digital Finance transformation, including the multi-year roadmap, finance systems, Workday governance, Snowflake data products, BI, AI automation, controls, and process redesign. Oversees finance data models, reporting standards, application architecture, business cases, vendors, budgets, and change management. Partners with Technology, the CFO organization, Risk, Audit, and senior leadership to improve financial insight, automation, adoption, and operational value while leading a multidisciplinary team.

Manages stress testing analytics, enterprise reporting, and risk data initiatives. Aggregates, maps, reconciles, validates, and analyzes large datasets; consolidates model results; applies analytical adjustments; and transforms complex outputs into visualizations and presentations for senior stakeholders. The role supports credit risk, loss forecasting, lending products, and stress testing while using Power BI, Excel, and PowerPoint, with potential Python, SQL, and SAS applications. It also provides analytical support, recommendations, and data-driven insights across technical and business teams.

Develop and productionize NLP and AI features for multilingual communications risk and compliance analysis. Design, fine-tune, evaluate, serve, and monitor transformer and LLM-based models, including RAG and embedding search. Own database architecture, data models, administration standards, testing, and infrastructure improvements supporting NLP pipelines. Collaborate with research, product, MLOps, engineering, and revenue teams; explain model behavior to clients and mentor engineers.

Develop and productionize NLP and LLM solutions for multilingual financial communications, including model training, fine-tuning, evaluation, RAG, and risk detection. Design and administer databases and data models supporting NLP pipelines, improve cloud infrastructure, document technical work, explain model behavior to clients, collaborate across research, product, MLOps, and engineering teams, and mentor engineers.

A 12-week unpaid fellowship providing hands-on training in Palantir Foundry and AIP. Participants attend live virtual instruction, complete technical projects, engage with Palantir engineers and leadership, and earn a professional certification. The program seeks builders with technical experience in software, data, automation, process improvement, prototyping, or related fields. Exceptional performers may interview for roles at Palantir or partner companies.

Leads channel operations and planning for the Canadian channel marketing organization. Responsibilities include designing process improvements, establishing promotional forecasting with demand planning, managing cross-functional projects, analyzing channel performance, developing dashboards and reporting frameworks, and translating data into actionable recommendations. The role partners with marketing, sales, finance, and planning teams to support strategic priorities, annual planning, forecasting, and business reviews.

Lead Samsara’s AI initiatives across the software development lifecycle, including developer agents and SRE AI. Manage five to ten senior engineers, set technical direction without an established roadmap, evaluate build-versus-buy decisions, control AI and infrastructure costs, scale automated incident response, and build trust in actions such as root-cause analysis, severity escalation, and deployment rollbacks. Partner directly with R&D leaders and developers while hiring, mentoring, and developing an inclusive, high-performing team.

Build agentic AI products that enable customers to create custom detections and workflows. Own solutions from customer discovery through design, implementation, deployment, monitoring, and ongoing improvement. Develop backend services, APIs, and customer-facing experiences while partnering with platform, machine learning, product, and design teams. Improve AI detection quality, reliability, performance, and cost, shape technical direction, and mentor engineers.

Lead the vision, strategy, and end-to-end lifecycle of Zip’s AI Contract Orchestration product. Develop features for clause analysis, redlining, contract generation, routing, metadata extraction, repositories, renewals, and compliance. Partner with customers, engineering, design, legal, procurement, and finance to improve contract cycle times and visibility. Own AI quality through evaluations, guardrails, feedback loops, and accuracy measurement while prioritizing roadmap investments and influencing stakeholders without direct authority.

Lead AI- and data-driven business transformation for North American customers across order-to-cash, procure-to-pay, inventory, and supply chain processes. Own value realization from discovery through ROI, develop executive narratives, manage stakeholders and global transformation workstreams, automate governance and project management with AI tools, and drive Celonis platform adoption. Partner with sales, value engineering, and customer leaders to build strategic roadmaps, enable change, and identify expansion opportunities.

Build and deploy secure, scalable software and AI solutions for legal workflows. Partner with legal customers to translate needs into technical products, develop production-grade Python services, evaluate LLM outputs, optimize prompts, and apply cloud-native, DevOps, and infrastructure-as-code practices. Mentor engineers, manage technical debt, and collaborate across engineering, product, legal, and design teams.

Leads Capital Markets Finance performance management, forecasting, resource allocation, financial insights, governance, and team development. Advises the Capital Markets CFO while modernizing reporting and analytical processes through automation, data, AI, and technology. Connects financial results with market developments, risks, opportunities, and strategic priorities, and leads technology use cases from concept through implementation and adoption.

Leads Microsoft Cloud and AI sales across financial-sector accounts in Canada. Responsibilities include managing sales teams, driving revenue and pipeline performance, executing complex enterprise deals, coaching sellers, forecasting, engaging C-level executives, developing account strategies, and collaborating with customer success, marketing, partners, and industry specialists. The role requires expertise in regulated-industry procurement, governance, compliance, competitive positioning, and large multi-stakeholder technology transactions.

Lead end-to-end data science and machine learning initiatives, including problem formulation, data preparation, model development, evaluation, deployment, and ongoing improvement. Build production-quality Python solutions using NLP, predictive modeling, anomaly detection, forecasting, and modern AI techniques. Collaborate with Product, Engineering, QA, and stakeholders to deliver customer-facing capabilities, diagnose model and data issues, establish evaluation frameworks, and mentor other data scientists.

Leads AstraZeneca Canada’s Respiratory and Immunology business unit, with full P&L accountability for a portfolio exceeding $500 million in revenue. Oversees commercial strategy, sales and marketing teams, launches, lifecycle planning, market access, medical and regulatory collaboration, compliance, digital innovation, stakeholder engagement, budgets, and organizational transformation. Manages more than 200 employees and develops senior leaders, succession plans, and cross-functional capabilities.

Lead a high-volume Scale Customer Success team serving mid-market and large commercial customers. Build segmentation strategies, digital and AI-driven engagement programs, playbooks, and lifecycle workflows to improve retention, expansion, adoption, and CSM productivity. Hire and develop CSMs, manage risk using data, collaborate with Sales and cross-functional teams, and personally handle critical customer escalations.

Supports client pilots, onboarding, and training for an AI legal technology platform. Designs and evaluates legal AI use cases, assesses output quality, translates user feedback into product improvements, and documents deployment best practices. The role requires legal exposure, strong communication, analytical judgment, adaptability, and enthusiasm for AI, prompt engineering, and workflow automation.

Advises enterprise clients on AI transformation, digital operating models, capability maturity, innovation opportunities, and transformation roadmaps. Builds relationships with executives, conducts stakeholder interviews and assessments, supports workshops, develops target-state capabilities, and prepares proposals, presentations, business cases, and engagement documentation. Tracks AI and digital trends, contributes to thought leadership, supports business development, and serves as a client point of contact throughout engagements.

Lead eBay’s data science and analytics function by setting strategic roadmaps, developing AI-enhanced metrics, predictive models, experimentation frameworks, dashboards, and growth solutions. Partner with senior business and product leaders to influence decisions, improve operational efficiency, and deliver measurable impact. Manage, mentor, recruit, and develop analytics talent while promoting an AI-first, innovative team culture.

Leads enterprise-wide AI governance, security, and continuous risk management. Designs AI risk assessment frameworks, maintains AI inventories and risk registers, evaluates AI models and third-party SaaS solutions, conducts adversarial security testing, and tracks governance maturity. Partners with architecture, legal, compliance, privacy, and technology teams to address AI-specific vulnerabilities, data exposure, bias, confidentiality, and regulatory risks.

Leads Sun Life’s global consumer insights measurement strategy and major multi-market research programs. Advises senior leaders by translating consumer feedback, behavioral data, research, and market trends into strategic recommendations for brand, marketing, innovation, and client experience decisions. Establishes research standards, oversees external partners, coaches team members, and embeds insights across Canada, the US, and Asia. Requires regular Toronto office presence and occasional early or late meetings to support Asian business partners.