Top Tech Jobs & Startup Jobs in Toronto

Owns vision, strategy, priorities, and lifecycle outcomes for a complex product or product portfolio. Partners with design and engineering to shape roadmaps, validate ideas, manage trade-offs, and deliver high-quality, compliant solutions. Uses customer, market, technology, and commercial insights to guide investment decisions. Leads cross-functional initiatives, develops junior Product Managers, and drives AI-enabled product experiences without direct people-management responsibility.

Leads the design, development, evaluation, and production deployment of large-scale search and information retrieval systems. Responsibilities include indexing and ingestion pipelines, traditional and LLM-based ranking, semantic and hybrid retrieval, query understanding, relevance evaluation, search infrastructure, and retrieval optimization. The role partners with engineering and product teams, advises leadership on search and AI strategy, develops self-service search platforms, publishes research, and mentors applied scientists and machine learning practitioners.

Provides technical leadership for cloud cost management and reporting platforms. Designs scalable software, APIs, data pipelines, and analytics solutions; establishes engineering standards; leads modernization, automation, security, observability, and CI/CD practices; and drives cross-functional initiatives. The role partners with product, FinOps, cloud platform, and business teams, mentors engineers, leads design reviews, and transforms cloud and AI cost data into actionable insights.

Creates and maintains authoritative tax advisory and compliance content; monitors legislation and Canada Revenue Agency guidance; analyzes and communicates complex tax developments; manages expert contributors and quality standards; collaborates on AI and tax-advisory initiatives; validates tax technology solutions; and provides feedback on AI performance. Requires deep tax expertise, strong writing and editing skills, bilingual French/English communication, technical adaptability, and at least seven years of tax advisory and compliance experience.

Sets technical direction for APIs that provide governed access to legal content for AI agents. Owns API architecture, retrieval and search design, MCP integrations, evaluation frameworks, reliability, observability, security, and platform governance. Leads cross-team architecture decisions, mentors engineers, manages operational responsibilities, and establishes AI-assisted, spec-driven development practices for a multi-team internal platform.

Build and deliver production backend, platform, and AI capabilities using C#/.NET and Python. Develop distributed systems, LLM applications, AI agents, retrieval workflows, MCP servers, document understanding, and scalable AI infrastructure. Provide hands-on Staff-level technical leadership through architecture, coding, technical direction, mentoring, deployment, reliability, safety controls, and production operations.

The Senior Research Engineer will develop and deliver scalable ML solutions, collaborate with teams, and apply innovative technologies in AI to impact professionals in legal and accounting fields.

Lead backend and AI orchestration systems for CoCounsel Audit: design and operate scalable, low-latency AI workflows, integrate LLMs and retrieval systems, mentor engineers, set platform strategy, and ensure reliability, observability, and auditability at production scale.

Lead product strategy and market fit for CoCounsel Tax, Audit & Accounting across corporate customers. Research customer needs, prioritize the roadmap, define enterprise workflows, and shape MCP/API-based AI platform capabilities. Partner with engineering, data science, subject matter experts, marketing, sales, and operations to launch technically complex products, improve onboarding, support enterprise security and compliance, and enable corporate go-to-market efforts.

Leads the design and development of cloud-native platforms supporting generative AI agents. Responsibilities include building backend services, developer enablement tools, CI/CD pipelines, Kubernetes and multi-cloud infrastructure, platform security, observability, DORA metrics, and production engineering practices. The role requires mentoring, architectural leadership, cross-functional collaboration, and expertise in cloud-native systems, networking, infrastructure as code, and systems programming.