Top Python Jobs in Toronto

Build and deploy AI agent systems that automate complex business processes. Analyze workflows, design and configure agents, integrate AI with enterprise applications, develop connectors and APIs, and establish evaluation and monitoring systems. The role requires expertise in cloud AI services, LLMs, NLP, Python, integration platforms, conversational AI, RAG, vector databases, APIs, and SQL/NoSQL systems. The engineer will also explore emerging AI technologies and mentor junior developers and system administrators.

Owns end-to-end reconciliation and financial reporting across card networks, banks, processors, and internal ledger data. Designs SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigates discrepancies, improves data pipelines, supports month-end close and audits, and partners with Finance, Accounting, Treasury, Tax, Compliance, Engineering, and Product. Mentors analysts and drives process improvements, automation, and responsible AI adoption.

Own corporate IT operations while automating identity and access lifecycles, SaaS administration, endpoint security, compliance evidence generation, and IT support. The role includes Okta and SCIM provisioning, MDM management, OS patching, encryption baselines, license reclamation, audit readiness, runbook standardization, and Tier 1/2 support. The engineer will use Python, Bash, APIs, and AI coding tools to replace manual processes with policy-driven workflows and advise Finance and HR on tool administration.

Designs, programs, integrates, troubleshoots, and maintains industrial automation systems for manufacturing assembly and packaging. Responsibilities include PLC control logic, industrial networking, HMI and SCADA development, system commissioning, root cause analysis, cybersecurity, MES/ERP integration, documentation, operator training, and preventive maintenance support. Collaborates with mechanical, electrical, IT, and production teams while ensuring safety and regulatory compliance.

Lead research and engineering work on LLM-based architectures for dialog, search, and destination entry. Optimize LLMs via prompting and fine-tuning, integrate them with ASR, TTS, and vision systems, and collaborate cross-functionally to deliver performant, resource-constrained solutions for automotive voice assistants.

Lead the architecture and hands-on engineering of Cloudbeds’ Snowflake and dbt data platform. Own data modeling, warehouse design, ingestion, orchestration, DataOps, CI/CD, governance, observability, performance, cost optimization, and AI/ML readiness. Mentor analytical engineers, evaluate emerging tools, establish data quality and security standards, and collaborate with engineering, infrastructure, data science, and business stakeholders in a fully remote environment.

Designs, builds, and operates Azure cloud infrastructure using infrastructure as code. Develops CI/CD pipelines, shapes end-to-end system architecture, troubleshoots production issues, builds internal automation tools, and maintains platform security, compliance, monitoring, backups, and reliability. The role also owns infrastructure projects through production and collaborates closely with software engineers.

Build and maintain reports, dashboards, scorecards, and analytical outputs. Analyze large datasets and business trends across product, onboarding, operations, revenue, sales, and customer experience. Use SQL, Excel, and BI tools to validate data, identify issues, improve reporting, and provide actionable recommendations. Partner with stakeholders to define metrics, support reporting cycles, document data processes, and contribute to automation and modern data platform initiatives.

Leads a three-person IT team and manages daily IT operations, employee support, SaaS platforms, device management, access administration, onboarding, offboarding, and technology adoption. The role improves ticketing, self-service, AI tooling, automation, and IT processes while partnering with Security, Development, and business leaders. It requires hands-on support expertise in a SaaS environment, strong communication, and practical decision-making.

Provides 24x7 operational support for mission-critical applications and infrastructure across Java, databases, cloud, containers, and networks. Monitors system health, investigates incidents, performs root cause analysis, supports releases and change management, and maintains operational documentation. The role also develops automation, improves observability, manages recurring incidents, and collaborates with development, infrastructure, network, and business teams across AWS, hybrid-cloud, and on-premises environments.

Architect, develop, and maintain scalable Java-based UI, API, microservice, and database test automation frameworks. Build reusable Selenium, TestNG/JUnit, Cucumber, and REST Assured solutions; implement BDD, TDD, shift-left testing, and CI/CD pipelines. Integrate AI and machine learning utilities for self-healing tests and predictive analytics. Debug complex automation, concurrency, and environment issues while collaborating with engineering and product teams in an Agile Scrum environment.

Develops, integrates, tests, debugs, and reviews low- to medium-complexity software for safety-critical railway signaling systems. Analyzes requirements, designs software components, performs integration and verification testing on simulators and hardware benches, investigates defects, conducts impact analyses, and supports field issue resolution. Collaborates with Systems Engineering to maintain software architecture and system consistency while following established development and safety processes.

Build and own the technical infrastructure supporting customer acquisition, attribution, lifecycle marketing, experimentation, analytics, and retention. Develop marketing data pipelines, API integrations, event tracking, automations, AI-powered marketing tools, attribution systems, landing pages, and internal growth tools. Diagnose funnels using SQL and analytics, improve data quality, and partner cross-functionally with Marketing, Product, Data, and Engineering to rapidly test and measure growth initiatives.

Drives enterprise AI adoption by identifying high-value automation opportunities, building secure AI-enabled workflows, integrating business systems and data sources, and establishing governance, monitoring, onboarding, and success metrics. Partners with Finance, Legal, HR, IT, Security, Engineering, and Data teams to scale reusable AI capabilities, support internal champions, and improve productivity, reliability, quality, and operational risk.

Leads an applications development team responsible for designing, implementing, and supporting software systems. Manages personnel, technical escalations, issue resolution, project execution, risk, budgets, compliance, and resource planning. Provides technical oversight across applications and advises developers and analysts. Requires strong Java/Spring Boot or Angular/React/Node.js expertise, software engineering knowledge, database experience, CI/CD and Agile practices, and familiarity with messaging, observability, cloud, and containerization technologies.

Own and evolve HOOPP’s investment data warehouse, pipelines, enterprise data model, and production support processes. Investigate data and platform issues, perform root-cause analysis, maintain data integrity and governance, and deliver sustainable solutions across investment, risk, finance, and technology teams. Develop AI-assisted projects using Python and related tools, improve monitoring and operational workflows, and manage access reviews, releases, documentation, and preventive actions.

Build and operate scalable AWS data foundations supporting analytics, search, and AI use cases. Develop structured and unstructured data pipelines using Snowflake, S3, lakehouse architectures, and distributed processing. Establish engineering standards, automated testing, infrastructure-as-code, CI/CD, data quality, lineage, and observability. Collaborate with data scientists, AI engineers, and business partners to productionize ideas, mentor engineers, and deliver secure, reliable, measurable solutions.

Own end-to-end reconciliation and reporting for card networks, banks, processors, and internal ledger data. Build SQL-based reporting, dashboards, exception queues, metrics, controls, and automated solutions; investigate discrepancies, improve data quality, support month-end close and audits, and partner with Engineering, Product, Accounting, Treasury, Tax, and Compliance. The role also defines requirements and test plans, maintains data pipelines, mentors analysts, and drives automation across payment settlement and money-movement processes.

Leads SEO strategy across client accounts, managing technical SEO, content optimization, AI Search visibility, audits, measurement frameworks, reporting, recommendations, and delivery quality. Builds client relationships, translates search data into business decisions, mentors junior consultants, supports pitches and account growth, and improves internal SEO processes. Requires strong technical SEO, analytics, client advisory, project ownership, and communication skills, with working knowledge of AI Overviews and LLM-powered discovery.

Lead SEO strategy for client accounts, owning technical SEO and AI discovery audits, measurement frameworks, recommendations, delivery quality, client relationships, mentoring, and account growth. Analyze data from search, analytics, crawling, ranking, log, and AI visibility tools. Guide technical, content, architecture, and visibility initiatives while managing workstreams, timelines, stakeholder communication, and practice improvements.

Build and scale technical systems for acquisition, experimentation, analytics, AI-powered outbound, content automation, website personalization, lead routing, CRM synchronization, and growth measurement. The role combines backend and frontend engineering with LLM workflows, data pipelines, attribution, A/B testing, and GTM integrations. Success means generating more qualified pipeline, improving funnel conversion, reducing manual work, and creating reliable, scalable growth systems.

Develops and maintains automated UI and API testing frameworks. Creates functional, regression, and end-to-end tests; builds testing tools; reviews requirements, test plans, and test cases; identifies defects, performs root-cause analysis, and improves QA processes. Collaborates with distributed stakeholders and uses GitHub and AI-assisted tools to improve test coverage and efficiency.

Lead reliability engineering for Braze’s NGINX ingress fleets, Kubernetes infrastructure, Ruby on Rails monolith, and Go API services. Design scalable, highly available systems; develop automated scaling routines; define SLIs, SLOs, and error budgets; conduct capacity planning; and participate in PagerDuty on-call rotations. Drive incident response, root-cause analysis, blameless retrospectives, runbook improvements, and resilient architecture decisions with product engineering teams.

Own the architecture and technical direction of Zynque, a live integration platform for supply chain and logistics. Scale throughput, reliability, and multi-tenant performance while customers onboard; establish observability, SLOs, incident practices, and capacity planning. Harden security, data integrity, and fault tolerance, eliminate scaling risks, mentor engineers, and partner with Product on platform investments. The role requires hands-on coding and ownership of enterprise readiness in a high-ambiguity environment.

Perform actuarial analyses, research, validations, and financial projections for P&C insurance. Develop monitoring reports, dashboards, and KPIs; collaborate with claims, legal, and operations; document actuarial conclusions; lead moderately complex projects; provide subject-matter expertise, mentorship, and process improvements while ensuring regulatory and risk control compliance.