Top Tech Jobs & Startup Jobs in Toronto

Build and support enterprise integrations and automations using Workato and Boomi, with emphasis on Legal systems. Design APIs, SFTP connections, ETL pipelines, AI agents, MCP servers, custom scripts, and employee-facing workflow tools. Manage secure platform environments, troubleshoot production issues, and integrate CRM, HR, Finance, Supply Chain, and Legal applications. Partner with stakeholders to gather requirements and provide production support and on-call coverage.

Build and operate large-scale infrastructure and data pipeline platforms. Responsibilities include developing automation, monitoring system health, improving reliability and scalability, managing cloud infrastructure, participating in design and production readiness reviews, planning capacity, documenting processes, and responding to incidents through on-call rotations. The role requires production software development, infrastructure tooling, data streaming and storage expertise, and experience optimizing distributed systems in public cloud environments.

Owns outside counsel and vendor billing operations, including invoice review, eBilling platform administration, guideline compliance, rate approvals, accruals, reconciliations, and dispute resolution. Partners with Legal Operations, Finance, attorneys, and law firms to maintain accurate legal spend. Develops spend analytics, dashboards, workflows, and playbooks while supporting platform improvements and broader legal operations initiatives.

Develop and maintain backend software for Lyft’s claims technology platform. Own features from product specifications through development, deployment, and maintenance; write tested, maintainable code; participate in code reviews; design scalable team-owned components; document technical designs; and collaborate with stakeholders and insurance partners to improve claims operations and reduce risk and costs.

Own Lyft’s B2B marketing technology stack, architecture, roadmap, integrations, data model, lead lifecycle, tracking, attribution, governance, reliability, and budget. Configure HubSpot, integrate CRM and data systems, improve workflows with AI, ensure privacy and deliverability compliance, lead cross-functional programs, provide technical direction, mentor support teams, and communicate strategy and risks to leadership.

Develop and deploy algorithmic and machine learning solutions for Lyft’s mapping products, improving route recommendations, traffic prediction, and travel-time estimates. Responsibilities include data exploration, feature engineering, experimentation, production ML systems, real-time inference, batch pipelines, monitoring, optimization, and metric development. The role partners with Engineering, Product, Operations, and Science teams to translate complex mobility and geospatial challenges into scalable solutions.

Lead analytics for Lyft’s airport marketplace by analyzing pricing, earnings, supply, cancellations, ride modes, and airport performance. Develop metrics, dashboards, models, reporting, and reusable analytical frameworks to identify growth and efficiency opportunities. Partner with product, engineering, marketing, design, and operations teams to turn insights into product decisions, and present recommendations and results to senior leadership and cross-functional stakeholders.

Use data science, experimentation, forecasting, and analytical frameworks to improve Lyft’s airport marketplace. Analyze large datasets, define product health metrics, identify growth opportunities, recommend technical and product solutions, and measure feature impact. Collaborate with engineering, product, design, and other scientists while presenting actionable findings to senior leadership and cross-functional stakeholders.

Develop backend Trust and Safety tools, features, and distributed systems that protect Lyft riders and drivers. Lead safety features from concept through launch, collaborate with product, design, policy, and engineering partners, write maintainable and tested code, participate in reviews and on-call rotations, and promote engineering best practices through knowledge sharing.

Lead the architecture and technical direction of Lyft’s mapping data platforms, including offline experimentation tooling, route simulation services, scalable pipelines, data governance, and observability. Own pipeline reliability and SLAs, evolve schemas, optimize SQL and data processing, build backend services and AI-assisted data tools, and mentor engineers. Collaborate with engineering, product, machine learning, and data science teams to improve routing quality and travel-time accuracy.