Top Python Jobs in Toronto

Build and ship AI-powered internal systems across investing, talent, founder services, finance, and operations. Projects include talent intelligence, sourcing and research tools, diligence workflows, firm knowledge search, operations automation, and reusable portfolio-company AI tools. The role requires end-to-end ownership, from identifying high-leverage problems and selecting the technical stack to building usable products, working with messy business data, and supporting portfolio founders with AI strategy and implementation.

Administers and supports enterprise infrastructure, Windows and Linux environments, Azure, Microsoft 365, virtualization, identity services, PKI, backups, and core banking systems. Automates processes, manages access and security remediation, supports disaster recovery, investigates root causes, maintains technical documentation, and provides Tier 3 and on-call support. Coordinates infrastructure projects, change management, vendor engagements, audits, and lifecycle planning.

Build Platform developers create reproducible containerized environments, AI-native verification systems, reliable testing infrastructure, developer tooling, backend mocks, asynchronous workflow testing, and service health scorecards. The role supports hundreds of engineers, modernizes libraries and CLIs, improves developer experience, and helps establish trustworthy, scalable software delivery practices.

Lead the technical vision and architecture of Coinbase’s FinHub financial infrastructure, including ledger, account balances, money movement, settlements, transfers, and transaction history. Drive distributed-system rearchitecture with double-entry accounting, idempotency, reconciliation, auditability, and resilient failure recovery. Lead cross-team initiatives, migrations, and technical strategy while partnering with product, finance, risk, compliance, and operations stakeholders. Mentor senior engineers and promote operational excellence and maintainability.

Design, build, and maintain pipeline and artist-facing tools across web, desktop, and Unreal surfaces. Develop Python integrations with Maya, Unreal, Nuke, Perforce, and AYON; build AI-assisted features; and own tools through production. Collaborate directly with artists and supervisors, manage work autonomously, and deliver responsive, maintainable, well-tested software.

Embed with clinical, product, and operations teams to deliver production AI features end to end. Build agentic systems using RAG, tool calling, MCP, and orchestration; establish evaluations, validation standards, monitoring, and governance; deploy solutions on the shared AI platform; and create reusable templates and tools. Partner with stakeholders in regulated healthcare environments while improving organizational AI fluency.

Develop and maintain manual and automated integration, functional, load, and performance tests for Akamai cloud APIs and identity services. Build Python automation frameworks, contribute to CI/CD infrastructure, review test automation, validate system scalability and security, and support release readiness. Collaborate with globally distributed developers, SDET engineers, architects, and program managers while testing Kubernetes-based cloud applications.

Define the architecture and technical direction of Coalition’s enterprise data platform. Build scalable Snowflake and dbt infrastructure, governed data models, batch and streaming pipelines, reusable data products, feature stores, semantic models, and AI data foundations. Establish standards for data quality, security, lineage, observability, and regulated workflows. Partner across engineering, product, underwriting, actuarial, security, and business teams while mentoring engineers and guiding cross-team architecture.

Build and own core components of an LLM-powered agent platform: orchestration, tool integrations, APIs, knowledge/memory infrastructure, trust & safety, and evaluation tooling. Partner with Operations to translate workflows into agent capabilities, mentor teammates, and ship production-ready, scalable AI-native systems.

Own end-to-end analytical functions for growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, analyses, and experiments; surface insights; and influence product, growth, finance, and operations decisions. The role requires strong independent data analysis, first-principles problem solving, clear communication, and ownership of ambiguous business challenges.

Own the analytical function for a business area such as growth, product, AI and automation, or strategic partnerships. Define business questions and metrics, build reports, analyze data, design experiments, communicate insights, and drive decisions and outcomes with cross-functional stakeholders. The role requires strong analytical thinking, independent problem-solving, persuasive communication, and end-to-end ownership of ambiguous business challenges.

Own end-to-end analytical work for a business unit spanning growth, product, AI and automation, or strategic partnerships. Define business problems, metrics, reports, experiments, and analyses; surface insights; communicate recommendations; and influence product, growth, finance, and operations leaders to drive measurable outcomes.

Own end-to-end data science for growth, product, AI and automation, or strategic partnerships. Define business questions, metrics, reports, analyses, and experiments; generate actionable insights; and influence product, growth, finance, and operations leaders. The role requires strong SQL or Python skills, independent analytical problem-solving, clear communication, and ownership of ambiguous, high-impact initiatives.

Leads enterprise Microsoft 365 transformation initiatives focused on SharePoint Online, Power Platform, Copilot, AI agents, automation, security, compliance, and governance. Architects and implements collaboration solutions, migrates legacy platforms, configures Purview and related controls, and develops AI governance strategies. Provides technical leadership, client engagement, workshops, training, and ongoing support while coordinating project risks and dependencies. Requires availability during Eastern Time business hours and deep Microsoft 365, security, programming, database, and cross-tenant migration expertise.

Own end-to-end DFT architecture and implementation for AI accelerator ASICs, including scan, compression, ATPG, MBIST, boundary scan, IJTAG, verification, and physical-design integration. Drive pre-silicon coverage, timing and power-aware test implementation, silicon bring-up, and cross-functional execution through tapeout. The role requires hands-on RTL, synthesis, gate-level verification, Tessent tool expertise, scripting, and failure analysis across multiple production tapeouts.

Design, build, ship, and support mobile SDK features for iOS and Android developers. The role involves writing high-quality, tested code, contributing across platform and hybrid SDKs, reviewing code, improving reliability, shaping technical direction, mentoring engineers, and helping prioritize the product roadmap. Engineers will work closely with customers and contribute to RevenueCat’s developer-focused monetization platform.

Build and scale real-time and batch data pipelines, data platforms, and analytics-ready datasets using Kafka, Databricks, Snowflake, Python, and SQL. Design modern data models, ensure data quality and observability, develop AI-powered data experiences, and support business-critical reporting and analytics. Collaborate cross-functionally, improve platform performance, champion engineering best practices, and mentor teammates.

Build and operate backend systems, APIs, integrations, automation workflows, and enterprise knowledge infrastructure for AI applications. Develop retrieval pipelines, vector database solutions, and agent-based systems while improving scalability, observability, reliability, and performance. The role requires production software engineering, modern AI architecture knowledge, clear documentation, testing, and collaboration with technical and nontechnical teams.

Lead technical execution for teams building endpoint agents, backend and inference services, cloud infrastructure, and customer-facing products. Translate engineering priorities into plans, milestones, and ownership; guide architecture and implementation; manage, mentor, and develop engineers; oversee planning, delivery, quality, hiring, and onboarding; and remove technical or resourcing blockers. The role requires hands-on technical judgment, distributed systems experience, and familiarity with agentic coding tools in a fast-moving startup environment.

Build customer-embedded solutions for Origin’s AI observability platform. Investigate customer traces and operational data using SQL, ClickHouse, APIs, and MCP tools; develop dashboards, integrations, workflows, prototypes, and production code; lead technical discovery; and translate field insights into reusable product capabilities. The role requires close collaboration with enterprise engineers, security teams, AI platform teams, and executives, with travel of up to approximately 20%.

Build and operate Origin’s AI observability platform across data-collection agents, backend services, infrastructure, inference pipelines, APIs, and React interfaces. Design distributed systems using AWS, EKS, ClickHouse, and Kafka for high-throughput, multi-tenant production workloads. Develop internal coding agents and define AI-native engineering practices while making decisions around storage, APIs, performance, and reliability.

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Leads an Investment Insights team creating analytics that improve investment manager effectiveness. Responsibilities include designing and developing investment analytics, researching methodologies, working with portfolio managers, productionizing solutions, applying AI, resolving complex analytical issues, and managing analysts across Canada and India. The role also shapes strategic priorities, develops team capabilities, mitigates process risks, and communicates technical concepts to varied stakeholders.

Designs and manages scalable data integration pipelines, governance controls, semantic enrichment, and orchestration systems for enterprise AI and analytics. Builds real-time data flows, APIs, connectors, RAG and embedding pipelines, vector database integrations, monitoring, audit trails, and AI guardrails. Partners with engineers, governance teams, and business stakeholders to make enterprise data secure, explainable, reusable, and ready for agentic AI workflows.

Maintains and validates performance, attribution, and risk analytics across systems; investigates data-quality exceptions; manages scheduled analytics processes; improves automation and scalability; strengthens analytics governance and controls; identifies and mitigates process risks; and serves as an analytics subject-matter expert and escalation point.