Top Software Engineer Jobs in Vancouver

Develop and deliver features for large-scale web applications using full-stack technologies across React, TypeScript, Node.js, Microsoft, and cloud stacks. Collaborate in agile Scrum or Kanban teams with architects, QA, product management, and stakeholders. Contribute to CI/CD, DevOps, troubleshooting, performance, security, and continuous improvement while building high-quality software solutions.

Build backend services, tooling, APIs, and infrastructure for deploying, testing, operating, and scaling AI agents. Responsibilities include Kubernetes operations, workflow orchestration, state management, CI/CD integration, observability, distributed systems reliability, performance optimization, and developer-experience improvements. The role collaborates with engineering, product, and AI teams while contributing to architecture and technical decisions.

Leads the design, development, testing, debugging, and operation of scalable distributed systems for Fabric data mirroring. Responsibilities include architecture, coding, code reviews, dependency management, telemetry and root-cause analysis, automated testing, reliability, security, performance optimization, and collaboration with technical and project stakeholders.

Designs and implements behavior planning systems for autonomous vehicles operating in structured, low-speed airport environments. Develops planning algorithms, decision-making modules, and scalable C++ and Python software; tests in simulation and real-world scenarios; optimizes performance and latency; and collaborates with autonomy and engineering teams. The role involves multi-agent interaction modeling, state machines, behavior trees, probabilistic planning, path planning, dynamic replanning, documentation, and system integration.

Build and ship backend software for Stripe’s Metronome infrastructure and financial automation products. Design scalable distributed systems, collaborate with infrastructure, security, design, and operations teams, mentor engineers, and troubleshoot production issues across services and system layers. The role requires strong coding ability, autonomy, and experience developing large-scale backend systems, with preferred exposure to event-driven architectures, billing, financial reporting, and engineering mentorship.

Build and improve reliable, scalable frontend experiences for Affirm’s pre-checkout products, including Affirm.js, promotional messaging, experimentation, and developer-facing tooling. Use browser debugging, monitoring, metrics, and testing tools to maintain accessible, performant cross-browser experiences. Collaborate with engineers and stakeholders, contribute to code reviews, troubleshoot operational issues, and write clear, well-tested, extensible code.

Design, build, and operate core components of Azure HorizonDB, a cloud-native PostgreSQL-compatible database service. Responsibilities include developing high-availability distributed storage, resiliency and recovery systems, automation pipelines, data migration tools, and performance improvements. The role involves on-call incident response, troubleshooting, cross-team technical collaboration, and applying AI-assisted engineering practices to improve software quality and operational excellence.

Build and maintain full-stack applications, AI agents, data pipelines, and analytical models for private equity teams. Partner directly with stakeholders to define solutions, manage delivery from scoping through production, and ensure data accuracy, lineage, reconciliation, and validation. Develop agentic workflows, document intelligence, APIs, and integrations using Databricks and Azure. Lead technical architecture, testing, deployment, documentation, and ongoing support while mentoring engineers and advancing engineering standards.

Build and deploy full-stack applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, evaluate AI-generated solutions for security and reliability, instrument products, analyze usage and outcome metrics, identify automation opportunities through customer conversations, and document effective prompts and development patterns.

Design, develop, test, optimize, and maintain foundational real-time video platform technologies. Diagnose complex camera, device, hardware, operating system, and media pipeline issues; improve performance, reliability, security, and efficiency. Collaborate across teams on architecture and technical projects, use telemetry and experimentation to analyze production behavior, participate in on-call incident response, and contribute through code reviews, documentation, mentoring, and engineering best practices.

Build scalable, high-performance backend systems, owning complex projects from planning through deployment. Collaborate with product and customer teams, contribute hands-on code, guide technical direction, review code, and provide architectural feedback while helping the company scale.

Build and deploy complete applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, instrument solutions, evaluate AI-generated output for security, privacy, reliability, and quality, and iterate based on usage and outcome metrics. Participate in customer conversations to identify automation opportunities and document effective prompts and development patterns.

Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering judgment, reasoning quality, usefulness, and correctness. Provide detailed written feedback, distinguish response-quality levels, define evaluation standards, and record short video explanations. This flexible remote contract requires strong software engineering experience, familiarity with AI-assisted development workflows, and the ability to make rigorous, opinionated judgments without reviewing every line of code.

Design, develop, test, and maintain scalable platform software and services. Collaborate with architecture and cross-functional teams, implement platform features, participate in code reviews, document technical specifications, troubleshoot issues, and optimize performance and scalability. The role requires Go development, scripting, Kubernetes, cloud-native technologies, containerization, cloud networking, and CI/CD experience.

Build experimental applications and interactive tools for configuring experiments, monitoring execution, visualizing results, and capturing metadata. Integrate instrument APIs with SDKs, data services, backend systems, and automation workflows. Implement testing, logging, failure recovery, CI, packaging, and deployment improvements. Diagnose issues across application, performance, concurrency, native-code, and hardware layers while collaborating directly with scientists and engineers to deliver reliable software.

Lead the design, development, scaling, and operation of Workday’s AI model-serving platform. Build distributed systems for traditional machine learning models and large language models, optimize Kubernetes and GPU infrastructure, improve reliability and observability, troubleshoot production issues, maintain CI pipelines, review code, write technical documentation, and mentor engineers while driving architectural decisions.

Lead technical direction and implementation of a large-scale AI model serving platform. Design, build, and operate distributed systems (Ray/Ray Serve), ensure scalability, reliability, monitoring (Prometheus), CI pipeline robustness, and evolve the production model registry while collaborating with ML engineers and stakeholders.

Design, develop, and maintain scalable RESTful APIs and core business systems. Reduce technical debt, optimize architecture, participate in code reviews, promote engineering best practices, and deliver small features through the full development lifecycle. Collaborate within an agile engineering team while troubleshooting problems and improving system stability and performance.

Lead the design, development, and technical strategy for high-availability financial services supporting Affirm’s card loan platform. Build scalable APIs, data models, microservices, and event-driven systems; troubleshoot performance and reliability issues; collaborate cross-functionally on loan attribution and lifecycle requirements; and mentor engineers through technical guidance, design reviews, and code reviews.

Own post-launch bugs, production issues, and enhancements for AI agents and related products. Investigate root causes across logs, code, conversation data, APIs, authentication, telephony, and integrations; implement and test fixes; support customers directly; guide frontline Support Engineers; and build internal tools that improve investigation and resolution speed.

Own production bugs, escalations, and enhancements for AI agent products. Investigate issues across logs, code, conversation data, telephony, integrations, authentication, APIs, and LLM prompting; implement, test, and ship fixes. Support customers directly, coordinate testing, guide frontline support engineers, build internal investigation tools, and relay feedback to Product while meeting SLAs.

Build and improve full-stack features for a legal AI platform. Responsibilities include frontend and backend development, responsive interfaces, data models, APIs, integrations, data pipelines, testing, deployment, observability, debugging, and performance improvements. The engineer will work directly with users, own projects end to end, make architectural tradeoffs, and help shape product direction in an early-stage company.

Design, implement, test, deploy, and operate highly available distributed services for Azure Monitor at global scale. Build telemetry collection, routing, storage, and data-access APIs and tools; improve reliability, security, observability, and diagnostics; and integrate machine learning and AI-assisted operational capabilities. Participate in on-call and incident response, collaborate across teams, mentor engineers, lead design reviews, and drive architectural alignment.

Build and operate backend infrastructure and APIs for stablecoin-based payments, deposits, withdrawals, and transfers. Own projects from system design through production, improve distributed-system performance and reliability, collaborate with Product, Design, Infrastructure, and Compliance, and contribute to engineering quality through reviews and architectural best practices. The role requires blockchain integration experience and responsible use of generative AI.

Build and scale AI-enabled developer experience, CI/CD, deployment safeguards, observability, and automated response systems. The role focuses on making software delivery autonomous, safe, reliable, and easier for engineering teams to adopt. Responsibilities include architecting enterprise-scale platforms, orchestrating AI agents, reducing technical debt and operational toil, partnering with product engineering teams, and establishing AI-native SDLC workflows. The engineer will also provide technical leadership and turn emerging AI capabilities into production-ready internal platforms.