Top Tech Jobs & Startup Jobs in Toronto

Leads a global AI engineering organization, owning multi-year strategy, product alignment, team transformation, vendor governance, and engineering operations. Oversees production AI lifecycle delivery, including retrieval, model integration, evaluation, deployment, monitoring, reliability, security, CI/CD, and AWS infrastructure. Establishes data-driven engineering metrics, AI adoption guardrails, cost controls, and responsible AI practices while partnering with product and technology leaders to deliver strategic initiatives.

Lead and manage a team building scalable full-stack legal research products, AI agents, retrieval-augmented generation systems, APIs, and cloud-native services. Provide hands-on technical leadership across architecture, coding, DevOps, security, reliability, and AI-assisted development. Hire, coach, and develop senior engineers while partnering with Product, Design, and stakeholders to deliver production-grade solutions on AWS.

Lead complex, cross-functional technology programs from initiation through completion. Own scope, timelines, budgets, resources, risks, governance, and benefits realization across concurrent projects. Engage senior executives, resolve dependencies, provide executive-ready reporting, and drive alignment across business functions. Improve PMO standards, methodologies, tooling, and AI-enabled practices while mentoring project managers and advising leadership on high-visibility delivery issues.

Leads the design, development, evaluation, and production deployment of document understanding systems for legal, tax, and accounting content. Responsibilities include semantic chunking, document enrichment, hierarchical classification, entity and citation extraction, knowledge graph construction, LLM post-training, model distillation, synthetic data generation, and evaluation framework development. The role guides architecture and AI strategy, partners with engineering on scalable delivery, influences leadership, and mentors applied scientists and ML practitioners.

Build, train, evaluate, and deploy production machine learning and LLM systems for legal document intelligence. Develop NLP solutions for information extraction, summarization, search, AI agents, and document analysis. Create scalable ML pipelines, evaluation frameworks, and reliability metrics while optimizing model performance. Collaborate with engineering, product, legal, data, and security teams to deliver secure AI capabilities and translate business problems into production solutions.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Designs and leads enterprise AI systems for legal research, including RAG pipelines, knowledge graphs, autonomous agents, and AI platforms. Provides technical strategy, architecture, mentoring, governance, testing, observability, and operational leadership. Partners with research, engineering, design, and product teams to launch scalable, secure AI products. Requires hands-on software engineering expertise in generative AI, cloud-native systems, APIs, distributed systems, and production AI deployments.

Own high-visibility AI transformation programs from strategy through delivery. Responsibilities include structuring ambiguous challenges, developing program plans, managing scope, budgets, risks, dependencies, and benefits, analyzing data and building business cases, maintaining PMO governance, leading cross-functional teams, and influencing senior stakeholders through steering committees and executive reporting.

Own the SafeSend product portfolio and lead its evolution into an AI-driven Gather & Deliver experience. Responsibilities include converging SafeSend and TaxCaddy, developing reusable workflow components, expanding APIs and integrations, enabling agent orchestration through CoCounsel, and delivering reliable tax-season performance. The role requires platform product leadership, customer migration expertise, AI product fluency, systems thinking, stakeholder management, and team-building skills.

Own the vision, strategy, roadmap, commercialization, and lifecycle of complex analytical products. Conduct market and competitive research, translate customer needs into requirements, collaborate with engineering, design, sales, and marketing, and lead go-to-market activities. Monitor adoption and performance, gather feedback, prioritize improvements, communicate with stakeholders, and guide AI-enabled product development. The role also coordinates cross-functional initiatives and balances strategic planning with tactical execution.