Top Software Engineer Jobs in Toronto

Design, develop, and lead Salesforce solutions using Apex, LWC, Flows, and integrations. Optimize performance within governor limits, enforce security and data models, implement CI/CD, and collaborate with stakeholders in Agile delivery as a technical/solution lead.

Design, build, and deploy AI/ML solutions including data pipelines, model fine-tuning, and production deployment. Develop real-time model-serving microservices, implement monitoring for drift and performance, collaborate with data and DevOps teams, and prototype LLM and generative AI solutions using structured and unstructured data.

Join a new Toronto engineering office and work across the stack building an agentic AI platform for enterprise accounting. Contribute to web development, databases, distributed systems, and frontend (TypeScript/React/Redux). Help define office culture and scale product and team.

Develop AI technologies for clinical trials, focusing on scalable ML infrastructure, optimizing models, and working cross-functionally to enhance safety and efficiency.

Build and maintain backend services for Offer/BIN experiences, lead Oracle (CATY) migration across services, improve reliability and observability, reduce technical debt, coordinate API and integration changes, and support safe rollouts through testing and monitoring.

Design and build software components for a distributed system, ensuring uptime and reliability while collaborating on project discussions and adhering to quality standards.

Develop and operate scalable backend systems for an AI-driven defense platform against digital threats, ensuring production reliability and collaborating across teams.

The Software Engineer, Infrastructure will develop backend infrastructure for scalable monitoring of digital threats using AI, enhancing systems for faster deployment and reliability.

Own and operate Baseten's internal AI stack, build and deploy custom AI agents and LLM-powered tools, evaluate third-party AI developer tools, instrument usage and measure impact on engineering productivity, and support engineering teams in adopting AI workflows.

The Principal Backend Software Developer will design and build core APIs and orchestration layers for an AI-assisted commerce platform, ensuring security and reliability, while leading cross-team initiatives and mentoring engineers.

Design, build, and deploy scalable AI/ML solutions: end-to-end pipelines, fine-tune LLMs, production model deployment with CI/CD, serve models via microservices/APIs, monitor model performance, collaborate with data/cloud teams, and prototype/evaluate new AI frameworks using Python, SQL, Spark and MLOps tools.

Build and maintain cloud-native services, APIs, and platform capabilities. Design, implement, test, and troubleshoot scalable SaaS/backend systems. Collaborate with product, UX, and engineering teams, participate in code reviews, agile delivery, and continuous learning.

Work as a backend Software Engineer building and maintaining microservices and APIs for customer-facing banking products. Participate in Agile Scrum teams, write high-quality code with unit and integration tests, perform debugging and root-cause analysis, follow secure coding practices, use source control, and contribute to documentation and team knowledge sharing.

Design, build, and maintain accessible, secure, and performant iOS mobile applications. Translate product requirements into well-tested code, integrate with backend services/APIs, troubleshoot issues, and collaborate with Product, Design, and QA. Participate in design discussions, code reviews, and continuous learning to improve user experience.

Design, build, and consume REST APIs and integration solutions using Spring Integration. Develop microservices on Azure with messaging/event-driven, asynchronous patterns. Work with relational databases (SQL Server/Oracle), implement OAuth2/JWT/SAML auth, and perform data transformations between JSON, XML, and CSV.

Develop and modernize full-stack applications (React, Node.js) and existing .NET/Java systems. Collaborate across SDLC with product, architects, and senior engineers. Perform security audits, incident investigations, and continuous improvements. Use agile practices and AI tools to improve development speed and quality.

Lead architecture and development of Group Benefits Experience applications using React, Node.js, GraphQL and cloud platforms. Drive modernization of .NET/Java systems, improve CI/CD, testing, observability, and reliability. Mentor engineers, collaborate across teams, and champion responsible AI to accelerate delivery while maintaining security and quality.

Lead technical design and delivery of end-to-end mainframe solutions. Develop, configure, integrate, deploy and support scalable, secure applications; produce system design specifications; provide platform administration and release management. Collaborate with architects, stakeholders and senior tech teams, focusing on payments/domain requirements (card/debit/credit, payment networks, PCI/EMV).

Design, build, and maintain automated test frameworks and suites (UI, API, backend, database). Execute regression and end-to-end tests, validate REST services, integrate tests into CI/CD, track defects, and coach junior engineers. Collaborate in Agile teams to analyze requirements, create test plans/cases, and improve automation and delivery processes.

Design, develop, test, and maintain full-stack distributed software systems. Work with Java/J2EE technologies, databases (MySQL/JDBC), Windows and Linux servers, network protocols (HTTP/HTTPS/TCP-IP), and collaborate across teams to deliver secure, accessible cloud-based solutions.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

Design, develop, and maintain scalable, secure full‑stack solutions (Java backend, Angular frontend) on Azure. Lead feature development, testing, CI/CD, observability, incident response, code reviews, and architecture decisions. Mentor engineers, collaborate with stakeholders, and drive operational excellence and continuous improvement. Knowledge of AI chatbots is an asset.

Build and maintain full-stack web applications using Vue.js/Nuxt 3, TypeScript, Node.js, and AWS. Implement SSR, reusable components, Node APIs and integrations with headless CMS and third-party platforms. Contribute to AI-enabled marketing workflows, performance, accessibility, SEO, testing, monitoring, and troubleshoot across browsers, APIs, CMS, and cloud infrastructure. Participate in code reviews, documentation, and cross-functional planning.

Lead architecture and implementation of a unified, cloud-native data feed platform. Design scalable ingestion, transformation, and delivery pipelines; establish DataOps, governance, monitoring, CI/CD, and performance best practices; mentor engineers and influence cross-team technical strategy.

Build and maintain Python-based, cloud-native data pipelines and file delivery systems on AWS. Design scalable delivery for CSV/Parquet/JSON via S3, SFTP, and data marketplaces. Implement data quality, monitoring, CI/CD, and migrate legacy feeds to cloud architecture. Contribute to web-based monitoring/configuration, documentation, reviews, and production support.