Top Tech Jobs & Startup Jobs in Toronto

Own the vision, strategy, roadmap, requirements, KPIs, and go-to-market execution for insurance-focused data products. Collaborate with engineering and data science teams on products, proofs of concept, and demos; communicate progress to executives; and ensure compliance with BFS regulatory, risk, and compliance requirements.

Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.

Develop and refactor Python optimization algorithms using object-oriented programming for supply chain, inventory allocation, replenishment, and pricing optimization. Build predictive models, apply advanced statistical and optimization techniques to large datasets, and deliver data-driven solutions for retail and CPG clients. Collaborate with business stakeholders and data science teams, communicate analytical insights, coach colleagues, and apply current data science practices to business problems.

Leads Agile delivery across multiple teams or complex value streams, facilitating Scrum ceremonies, coaching teams, resolving impediments, managing dependencies and risks, and aligning stakeholders. The role oversees backlog and sprint goals, delivery metrics, release and change management, governance, reporting, and continuous improvement. Experience with analytics programs, cloud platforms, and tools such as Azure DevOps, Jira, Confluence, and Miro is valuable.

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.

Manage analytics consulting projects from problem definition through solution delivery. Translate client business challenges into analytics designs, apply statistical and machine learning techniques, present insights to executives, and develop plans to operationalize solutions. Collaborate with global consulting, IT, and data engineering teams while managing stakeholders and project teams.

Designs and deploys enterprise knowledge graph solutions, semantic models, ontologies, taxonomies, and data governance frameworks. Establishes metadata management, lineage, business glossaries, stewardship workflows, and data quality standards. Collaborates with business, AI/ML, and engineering teams to translate domains into scalable architectures and integrate graphs with data fabrics, data meshes, and AI systems. Serves as a technical authority on client deployments and converts ambiguous requirements into production-ready data architecture blueprints.

Looking for a Data Engineer experienced in Dataiku to design and maintain data pipelines and infrastructure, ensuring data flow and integration across teams.

The Data Engineer will architect and implement advanced analytics capabilities, manage data pipelines, and optimize data processing using AWS cloud and various analytical tools.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.