Top Software Engineer Jobs in Vancouver

Design, develop, test, and maintain scalable software solutions for a high-volume WMS platform. Troubleshoot production issues, perform root-cause analysis, implement CI/CD and telemetry, lead small engineering groups, mentor engineers, and collaborate with product and UX teams to deliver high-quality, maintainable code and APIs.

Lead architecture and delivery of cloud-native, distributed AdTech platform capabilities. Drive technical execution across teams, integrate AI/ML, ensure high availability, oversee full SDLC, mentor engineers, and collaborate with stakeholders to align engineering with business goals.

Lead and execute perception R&D and engineering for factory robots: define multi-year roadmap, architect perception pipelines (detection, segmentation, 6-DoF pose, scene understanding), drive sensor fusion and calibration, establish data/model workflows and deployment practices, integrate with planning/control, hire and mentor engineers, and evaluate research for production adoption.

Develop, implement, and support enterprise software using Java/Spring Boot and Angular. Collaborate with product and agile teams to design, code, test, review and deploy microservices and APIs, provide production support, document artifacts, and ensure scalability, performance and adherence to architecture and best practices.

Build, operate, and extend Affirm's data platform and application tooling to enable self-service data applications at scale. Implement platform features (provisioning, CI/CD, access control), integrations, data governance, automation, observability, and on-call operations. Contribute to roadmap for semantic layers, agentic data tooling, and AI-native workflows while raising engineering and operational standards.

Lead large-scale, cross-functional engineering projects to deliver AI-native SaaS features. Own platform architecture for multi-tenant, cloud-native systems, drive engineering standards and developer tooling, mentor engineers, and operationalize LLMs, agent frameworks, and real-time data in production.

Build automated reliability and self-healing platform tooling to protect production at scale. Improve incident management, reduce alert noise, evolve observability (monitoring, SLOs, performance detection), and develop AI-driven operational automation. Partner with product teams to diagnose reliability gaps, drive incident prevention, and champion operational excellence and best practices across engineering.

Build and own secure, event-driven full-stack services on AWS using TypeScript/Node.js. Implement infrastructure-as-code, CI/CD, observability, REST APIs, and automated tests; respond to production incidents and participate in architecture decisions while leveraging AI tools.

Build and ship full‑stack features for North, an enterprise AI workspace. Develop secure autonomous agents, execution engines, integrations, observability and evaluation systems. Collaborate with researchers to productionize models and deliver performant, low‑resource deployment code while adhering to strict security and privacy constraints.

As a Machine Learning Engineer, you will develop models for NLP and code-generation systems, analyze data, and improve AI performance using advanced algorithms. You'll manage the entire ML lifecycle and ensure effective communication of model benefits across the organization.

Develop and maintain scalable, reliable back-end systems and APIs, write maintainable code, and collaborate with global teams in a hybrid work environment.

Design and develop user interfaces and backend architectures for web applications, ensuring seamless integration and optimal performance using modern web technologies.

The Connector Software Engineer will design, develop, and maintain software connectors for API and database integrations, focusing on data security and interoperability in enterprise systems.

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.

As a Frontend Engineer, you'll craft user interfaces, write engineering requirement documents, build test suites, and integrate analytics for product success.

As a Backend Engineer, you will design scalable APIs, create Engineering Requirement Documents, and build test suites for product analytics and performance.

Develop and integrate software for hardware platforms using C/C++. Responsibilities include architecture definition, SDK integration, and system performance monitoring, while collaborating with various teams and mentoring new developers.

As a Senior Full-Stack Developer at gaiia, you will architect, develop, and manage critical systems in a serverless environment, collaborating on core modules related to customer management.

Develop scalable front-end and back-end features for a consumer-facing 3D/AR product using computer vision. Collaborate with product and design, own systems lifecycle, ensure performance and quality, unblock partners, and continuously learn and improve.

The role involves developing backend services using Python and Django, ensuring high availability and performance, and leveraging computer vision technology for 3D experiences in home decor.

Build scalable, high-performance front-end experiences using React/Next.js and Three.js, collaborate with product and design, own systems, integrate computer vision, and deliver polished UX for customers.

As a Senior Full Stack Software Engineer at Doxel, you will design and develop applications for project management, focusing on complex data handling and intuitive UI. Your role involves collaborating across teams and providing technical leadership in software projects.

Build full-stack features across a Next.js frontend and FastAPI backend, implement responsive React UIs, integrate AI-powered workflows and streaming responses, consume auto-generated OpenAPI clients, write tests and optimize performance, and collaborate on code reviews and product design.

Design, build and expand automated test coverage for a data-oriented ETL product. Learn the data model, create test plans, execute automated and manual tests (Pytest), analyze results, and ensure quality across cloud environments and multiple databases. Work within Agile and CI/CD pipelines.

Design and implement features for content ingestion pipelines, metadata services, and content processing workflows. Build reliable, observable services that handle diverse file formats, malformed inputs, retries, and asynchronous workflows. Collaborate with ML, Search & Discovery, and Product to improve metadata extraction, classification, and discoverability while leveraging LLM-based tools and AI-driven practices.