Top Software Engineer Jobs in Toronto

Design, build, test, and maintain production-quality applications and services using NestJS and/or Spring. Work with event-driven architectures and Kafka, use AI-assisted development tools, write maintainable code, collaborate with engineering and product stakeholders, participate in code reviews and troubleshooting, and contribute to technical decisions and continuous improvement.

Design, develop, test, integrate, maintain, and support complex enterprise web applications throughout the software development lifecycle. Work with C#, .NET, Angular, TypeScript, SQL Server, and related Microsoft technologies across multiple client projects. Contribute to architecture, technical decisions, documentation, quality standards, and problem solving while collaborating with distributed teams and maintaining strong client relationships.

Set technical strategy for backend identity decisioning systems, lead major engineering initiatives, and ensure highly available operations. Partner with product, design, and analytics teams; establish coding, architecture, monitoring, testing, and on-call standards; communicate technical decisions; and mentor engineers. Build and scale distributed systems supporting KYC, user lifecycle management, and identity decisions across international markets.

Build and operate applied AI systems, including LLM integrations, agentic workflows, data pipelines, evaluation frameworks, MCP tools, APIs, and governed content-serving layers. The role emphasizes production reliability, provenance, security, cost and latency management, regression detection, and human-reviewed AI outputs. Responsibilities include cloud deployment, structured content modeling, telemetry, governance, mentoring, and collaboration on AI standards. Strong Python, TypeScript, AWS, API, data pipeline, and production LLM experience are required.

Architects and ships production AI agent systems, including multi-component pipelines, tool integrations, orchestration infrastructure, observability, evaluations, and reliability practices. The role owns complex systems end-to-end, contributes to technical architecture and progressive delivery, collaborates across product and engineering, and mentors engineers. It requires strong backend, distributed systems, cloud infrastructure, LLM, and agentic development experience.

Design and deliver complex, scalable Salesforce solutions for customer implementations. Lead technical architecture, Apex and Lightning Web Component development, integrations, performance optimization, code reviews, and production issue resolution. Partner with customers and Product teams on requirements, solution design, technical roadmaps, and delivery. Mentor engineers, improve development processes and frameworks, manage project risks, and ensure high-quality, maintainable implementations.

Design, build, and deploy enterprise-scale agentic AI and generative AI solutions for banking. Develop full-stack LLM applications, integrate multiple model providers, establish evaluation and feedback systems, and prototype emerging AI technologies. Work in agile squads using MVP-driven delivery while ensuring security, resiliency, scalability, and regulatory alignment. Mentor junior engineers and collaborate cross-functionally on production-grade AI capabilities.

Leads the long-term technical health of Carta’s Investors business unit by solving ambiguous, complex problems; driving architectural improvements for scalability and reliability; aligning teams on technical decisions; defining safe AI engineering practices; and mentoring senior engineers. The role focuses on distributed systems supporting fund financials, tax and compliance, LP management, and reporting.

Leads technically complex software projects from concept through production, improving system performance, reliability, and simplicity. Mentors engineers through code reviews and architectural guidance, collaborates with product and design, and applies modern AI-assisted engineering tools. The role supports Carta’s Investors platform, including fund financials, tax and compliance, LP management, reporting, ledgers, reconciliations, and capital calls.

Lead software engineer responsible for designing and developing robust, automated technology solutions for margin and collateral platforms. The role involves building RESTful APIs, event-driven microservices, and user interfaces; collaborating with product teams and users; applying TDD and clean-code practices; and solving complex engineering problems in a global financial technology environment. Cloud, distributed systems, and financial services experience are beneficial.

The role involves designing and developing core features for the Linux sensor in CrowdStrike's security platform, collaborating with teams across the company, and maintaining software quality for cross-platform delivery.

Develop and maintain open-source client code and backend services focused on networking features. Design, test, document, and optimize distributed networking components, improve scalability and stability, support observability and incident response, handle customer escalations, and apply security-first engineering practices. Collaborate asynchronously with engineers, product managers, and UX/UI designers throughout the product lifecycle.

Develop and maintain scalable Java applications and REST APIs using Spring Boot. Write clean, efficient code, automate tasks, test using TDD, troubleshoot systems, monitor performance, and collaborate with internal teams and vendors. Review code, validate software, apply current technologies, and contribute to product improvements. The role may also involve cloud platforms, containers, CI/CD, security protocols, UI frameworks, on-call support, and mentoring.

Design and lead enterprise AI systems using generative AI, RAG, knowledge graphs, and autonomous agents. Define technical strategy, evaluate emerging AI technologies, and guide architecture and roadmaps. Mentor engineers, champion MLOps and LLMOps governance, and ensure security, testing, monitoring, and observability. Collaborate with research, engineering, design, and product teams to deliver scalable customer-facing solutions while optimizing latency, cost, and user experience.

Designs and leads enterprise AI systems for legal research, including RAG pipelines, knowledge graphs, autonomous agents, and AI platforms. Provides technical strategy, architecture, mentoring, governance, testing, observability, and operational leadership. Partners with research, engineering, design, and product teams to launch scalable, secure AI products. Requires hands-on software engineering expertise in generative AI, cloud-native systems, APIs, distributed systems, and production AI deployments.

Lead observability engineering for the Auth0 Platform by building and maintaining metrics, logs, traces, alerting, and instrumentation infrastructure. Provision cloud-native services with Terraform, troubleshoot performance and operational issues, support incident response, improve platform availability, and establish observability standards across engineering teams. Mentor engineers and lead cross-functional initiatives involving Datadog, OpenTelemetry, containerized services, and scalable production systems.

Develop and optimize high-performance features for SideFX’s 2D and 3D software products, including Houdini and Houdini Engine plug-ins. Maintain the glTF importer and exporter, support PDG, HAPI, games tools, and multiple hardware platforms, and debug product issues. The role requires modern C++ and Python development, strong 3D graphics knowledge, software quality and performance focus, independent problem-solving, and effective collaboration.

Design and scale Cohere’s Model Vault backend and inference platform. Lead architecture for authentication, deployments, billing, metering, customer lifecycle, and cloud control-plane services. Build reliable distributed systems with strong guarantees for security, privacy, consistency, isolation, observability, and failure recovery. Drive technically complex initiatives from threat modeling and architecture through implementation, production rollout, operations, and iteration at enterprise scale.

Develop and maintain large-scale software systems, including module and subsystem analysis, implementation planning, code reviews, QA specifications, stress and scalability testing, troubleshooting, and technical documentation. The role also involves collaborating with customers to define requirements and supporting payment-related technologies, including EMV, ISO 8583, secure algorithms, payment terminals, and smart card systems.

Develop and maintain large-scale software, including module and subsystem analysis, implementation planning, code reviews, QA specifications, stress and scalability testing, troubleshooting, customer requirements gathering, system documentation, and test strategy development. The role requires expertise in C/C++, Windows APIs, networking, payment protocols, SQL, and secure transaction technologies. Experience with EMV, smart cards, payment terminals, and certification is advantageous.

Own the customer-facing user experience and workflows for mCloud. Build performant React dashboards, topology visualizations, telemetry and alert views, gateway management tools, and administrative workflows. Collaborate with Product, Design, Backend Engineering, and other teams to integrate GraphQL and REST services, improve reliability and observability, and use AI-assisted development tools to accelerate component, query, and test creation.

Build and maintain developer tools, SDKs, CLI, MCP interfaces, integrations, and supporting backend services. Collaborate on API contracts, compatibility, testing, releases, documentation, and shared tooling. Support developers through GitHub issues and pull requests while designing reliable systems with authentication, retries, idempotency, rate limits, monitoring, and error recovery.

The role involves optimizing hardware support within a software stack for AI model deployment, collaborating with teams and hardware vendors to enhance performance and portability across platforms.

Build full-stack features for an AI-powered insurance application using Python, React, Redux, PostgreSQL, and AWS. Integrate and deploy AI/ML models, develop data pipelines, design scalable cloud architectures, and create user experiences around intelligent functionality. Participate in architecture planning, code reviews, releases, cross-team collaboration, and engineering initiatives while researching new AI applications.

Provides expert technical support for Android framework and core OS issues on Zebra mobile computing products. Debugs AOSP source code, NFC stacks, Host Card Emulation, secure elements, and RFID HALs; collaborates with customers and hardware, firmware, software, and product teams. Develops AI-driven diagnostic and workflow automation tools, documents solutions, and mentors support engineers.