Top Python Jobs in Toronto

Lead technical discovery, customized demonstrations, and proofs of value for enterprise CTEM customers. Map vulnerability, asset, ticketing, and remediation workflows; integrate customer tools; prove exposure-management outcomes using customer data; and communicate findings to engineers, CISOs, and executives. Maintain presales deal information, provide product feedback, create reusable demo and POV assets, and expand expertise into third-party risk management and cyber risk quantification.

Support Web3 users and technical operations across Telegram, Discord, blockchain infrastructure, RPC services, and AI-powered support workflows. Triage node and synchronization issues, develop and troubleshoot Telegram Bots and Mini Apps, maintain knowledge-base content, coordinate urgent issue resolution, and document solutions. The role requires blockchain fundamentals, programming ability, technical troubleshooting, responsive communication, and five-day weekly availability.

Own LanceDB’s marketing operations systems, data, lead management, routing, scoring, attribution, campaign execution, event operations, and pipeline reporting. Build an open-source qualified lead program using product and community signals, maintain data hygiene and governance, support ABM infrastructure, and improve marketing workflows with AI and automation. This senior, hands-on role partners with Sales, RevOps, Product, Engineering, and company leadership to establish scalable marketing processes from the ground up.

Lead ownership, harden, and operate an AWS-native backend/platform: build APIs, event pipelines, data services, compliance features (audit logging, encryption, data lifecycle), deployment automation, testing/acceptance tooling, and shape architecture and engineering hiring.

Lead client-facing integrations and implementations for an AI-native, compliance-focused travel platform. Design, build, and operate backend services, event pipelines, and data services on AWS. Ensure auditability, encryption/key management, consent and data lifecycle handling, and translate client feedback into product improvements while shaping architecture and early hiring.

Build and maintain Linux distribution packages, container images, CI tooling, and release infrastructure for GitLab. Enable development teams to integrate components through self-service tooling and documentation. Manage cloud marketplace integrations, installation and upgrade processes, dependency security, license compliance, and partner validation. Collaborate with development and security teams while reviewing external dependency and security updates.

Build and operate a developer platform for independently versioned modules across global compliance sites. Responsibilities include CI/CD and GitOps automation, reproducible builds, artifact provenance and signing, dependency graph and change-impact tooling, Kubernetes controllers, site provisioning, version management, security patch automation, and large-scale selective test orchestration.

Lead AI coding-tooling standards and developer experience, define Skill Marketplace conventions, and build production-quality internal AI application prototypes. Develop reference implementations for agent workflows, streaming UX, memory, multi-agent collaboration, and AI-native engineering processes. Provide architecture guidance, review code, publish technical content, deliver workshops, and collaborate asynchronously with APAC teams. The role requires strong full-stack engineering, product judgment, LLM application experience, and public technical influence.

Designs and maintains cybersecurity controls across IT, cloud, network, and industrial environments. Responsibilities include security monitoring, incident response, SIEM/EDR management, vulnerability management, firewall and segmentation configuration, Zero Trust implementation, ISO 27001 audits, risk assessments, vendor security, awareness initiatives, reporting, and continuous improvement. The role collaborates with technical and business teams, supports security tool deployment, and provides emergency assistance outside regular business hours.

Lead Affirm’s enterprise AI security review program, threat-model AI and LLM applications, assess agentic systems and tool permissions, and design automated guardrails, controls, monitoring, and policy-as-code. Review code, prompts, configurations, vendors, and SaaS AI capabilities; develop testing and red-team scenarios; identify emerging vulnerabilities; support incident response; and lead cross-functional initiatives across Security, Engineering, Legal, Privacy, and Compliance.

Designs and delivers customer-facing AI transformation engagements, including strategy sessions, workshops, architecture design, and rapid prototypes. Leads solution architecture, discovery, strategic planning, cross-platform cloud integration, and technical sales collaboration. Advises customers on Azure AI technologies, application architecture, security, scalability, and performance while coordinating cross-functional teams. Builds technical expertise in Azure AI Foundry, Microsoft Fabric, agentic AI, DevOps automation, and emerging technology trends.

Lead and develop a software engineering team building institutional investment transfer platforms. Responsibilities include hiring, coaching, technical direction, roadmap planning, reliability and scalability improvements, operational automation, cross-functional delivery, engineering best practices, incident response, and AI-assisted development. The role partners with Product, Design, Operations, CX, Infrastructure, Security, and SRE teams in a complex financial technology environment.

Own and expand Wagmo’s AI-powered claims automation pipeline. The Senior Software Engineer will improve model routing, reduce processing costs, increase automation accuracy, modularize and evaluate pipeline stages, and ship production AI features that support real financial claims decisions. The role requires strong Python skills, experience with production LLM systems, system refactoring, model-cost tradeoffs, and close collaboration with Product.

Provides expert-level support within a 24x7 security operations center, leading complex customer escalations and high-impact investigations. Builds automated case playbooks, training materials, and knowledge content; troubleshoots security tooling and services; performs root-cause analysis; and partners cross-functionally on improvements. Audits support quality, coaches analysts, and applies expertise in endpoint, SIEM, cloud, identity, network, phishing, threat detection, AI, and incident response practices.

Build and deploy end-to-end statistical and machine learning solutions for clients and internal delivery teams. Responsibilities include scoping ambiguous problems, analyzing operational challenges, prototyping AI workflows, translating messy data and real-world constraints into scalable solutions, iterating with stakeholders, and developing reusable tooling and infrastructure. The role combines hands-on data science with technical consulting and requires communication with technical and non-technical stakeholders.

Lead end-to-end data science and machine learning projects, from scoping ambiguous client problems through production deployment. Build and evaluate statistical and ML models, analyze large datasets, run experiments, collaborate with engineers, create reusable tooling, communicate findings to diverse stakeholders, and mentor data scientists. The role combines hands-on data science with technical consulting and requires occasional customer on-call support.

Create and maintain developer documentation, tutorials, API references, troubleshooting guides, and runnable examples for LanceDB. Build documentation designed for both developers and AI agents, validate AI-generated content, maintain documentation tooling, automate code and link checks, and collaborate with engineering, product, and open-source communities. The role requires strong Python skills, database and data workflow knowledge, technical writing expertise, and experience with Git-based development workflows.

Owner of a portfolio of large regulated Partner accounts, responsible for revenue expansion, account strategy, and technical growth interventions. Combine account leadership, hands-on engineering (SQL, Python/Node, JS/TS, Vue/React), experimentation (A/B testing), and cross-functional collaboration to diagnose performance, build and ship fixes, and codify repeatable growth playbooks.

Build production AI systems for finance teams, including customer-specific anomaly-detection models, grounded natural-language generation, agentic workflows, and managed LLM integrations. Develop Python services with warehouse access and customer-hosted deployments. Implement verification, human-confirmation checkpoints, anti-leakage controls, and CI evaluation for grounding and hallucination. Use customer feedback to improve models and systems while collaborating with AI and evaluation engineers.

Build and own production-grade data pipelines, source connectors, warehouse transformations, curated data models, reconciliation, and lineage for an AI-native finance platform. Develop dbt projects, orchestrate reliable and rerunnable workflows with Airflow or Dagster, tune warehouse performance, integrate messy enterprise systems, and ensure data correctness, auditability, and tenant isolation. Collaborate with backend and AI teams, establish data contracts, review work, and mentor engineers.

Design and build deterministic, auditable AI engines and conversational agents for finance platforms. Lead architecture across RAG, agent orchestration, structured outputs, grounding, evaluation, verification, and human-in-the-loop workflows. Develop production Python services with SQL and vector retrieval, support multi-cloud and on-premises deployments, mentor engineers, conduct design reviews, and communicate architecture decisions to technical and business stakeholders.

Designs and implements DFT architectures and specifications for ASIC/SoC products. Responsibilities include scan insertion, ATPG pattern development, compression and clock-control insertion, optimizing test coverage and power, and pre- and post-silicon verification and debug. The role also requires gate-level simulation, failure analysis, scripting, and collaboration across product teams.

Design and build scalable backend systems, APIs, data models, event-driven services, experimentation platforms, and personalization systems. Partner with Product, Data Science, Analytics, and Design teams to support customer acquisition and engagement. Establish secure, observable, high-performance engineering practices, mentor junior engineers, and participate in monitoring, on-call, and operational support.

Design and implement scalable, fault-tolerant security solutions protecting enterprise data across clouds, SaaS applications, and AI agents. Build agentic security capabilities, integrate large-scale third-party data sources, develop RESTful APIs and microservices, optimize distributed systems, and create secure software resilient to attacks and high-volume endpoint communication.

Analyze product usage and telemetry data to identify trends, opportunities, and product improvements. Partner with Product Analytics, Data Science, and product teams to define success metrics and measurement plans. Build dashboards, reports, and self-service analyses using SQL and analytics tools, validate telemetry and data quality, and communicate findings through written analyses, presentations, and recommendations.