Top Software Engineer Jobs in Vancouver

Develop and customize Infor LN applications, integrate payment gateways and third-party systems, and build full-stack web applications. The role includes creating APIs and backend services, integrating front-end interfaces with ERP functionality, troubleshooting LN environments, participating in code reviews, collaborating with stakeholders, and improving development processes. Candidates need Infor LN development experience, full-stack skills, ERP module knowledge, integration expertise, and familiarity with cloud, DevOps, and CI/CD practices.

Design, build, deploy, and iterate on full-stack product capabilities for AI-powered commercial intelligence software. Develop React and TypeScript user experiences, real-time AWS Lambda services, scalable APIs, and backend systems across AWS, Kubernetes, Snowflake, PostgreSQL, DuckDB, and DataFusion. Lead technical design and reviews, mentor engineers, improve testing and observability, guide AI coding agents, and contribute to technical roadmaps.

Build and operate scalable full-stack features for Evisort’s AI-driven contract management platform. Collaborate with engineering, data science, product, and design teams to deliver user-centric SaaS solutions. Own functional areas from development through production, contribute to architecture and roadmap decisions, mentor teammates, and apply modern engineering practices including distributed systems, DevOps, CI/CD, automated testing, containerization, and observability.

Develop custom customer integrations and provide Bubble.io guidance. Build and maintain Salesforce, HubSpot, and other CRM integrations; manipulate data with Python and Pandas; design AWS Lambda microservices; support client onboarding and collaborate with the development team to improve the platform.

Lead backend engineering for capacity modeling systems that forecast traffic, resource needs, and infrastructure scaling. Own quarterly team goals, guide engineers through complex problems, collaborate with product and analytics stakeholders, improve code and design standards, monitor system availability, support on-call operations, and develop team talent. Build highly available distributed systems, tune autoscaling and compute performance, and deliver scalable features using Python or Kotlin, AWS, MySQL, and Kubernetes.

Build and enforce workload safety standards across Affirm’s Amazon EKS fleet. Responsibilities include Kubernetes resource management, workload isolation, disruption handling, cluster capacity planning, policy automation, production debugging, and fleet-wide infrastructure improvements. The role leads cross-team initiatives, mentors engineers, participates in Kubernetes runtime on-call, analyzes resource profiles, and measures impacts on availability, latency, risk, and cost.

Lead full-stack software development with a primary focus on Java, including architecture design, coding, code reviews, performance optimization, documentation, DevOps, Azure cloud deployment, and mentoring engineers. Collaborate with product and business partners to deliver scalable solutions, establish technical roadmaps, enforce engineering standards, and improve system reliability and development processes.

Build and own Keycard’s infrastructure platform, including bring-your-own-cloud deployments, multi-tenant and single-tenant cells, infrastructure as code, Kubernetes operations, releases, upgrades, observability, security guardrails, and audited break-glass workflows. Develop tooling and agents for installation, diagnostics, and operational support. Define compatibility matrices, deprecation policies, and upgrade processes while partnering directly with enterprise cloud and security teams.

Develop and maintain the Keycard Agent SDK, ensuring compatibility with various languages and frameworks, while engaging with the developer community to enhance agent applications.

Develop and maintain backend systems and full-stack software using PHP and Node.js, including containerized microservices on AWS Kubernetes. Responsibilities include system design, coding, testing, code reviews, troubleshooting, deployments, production support, and technical guidance. The engineer collaborates with product owners, project managers, DevOps, QA, and data engineering teams throughout the software development lifecycle, emphasizing reliability, performance, maintainability, and automated testing.

Designs, develops, and deploys agentic AI systems for cybersecurity, including vulnerability analysis, threat detection, alert triage, secure code generation, and remediation recommendations. Builds RAG pipelines, LLM integrations, APIs, microservices, and cloud-based platforms. Implements AI guardrails, threat modeling, human-in-the-loop governance, adversarial testing, explainability, and performance optimization while integrating systems with SIEM, SOAR, vulnerability management, and endpoint security tools.

Build and operate production Python services, AI-enabled workflows, RAG systems, multi-agent applications, and security automation platforms. Automate threat modeling, policy Q&A, vulnerability analysis, and code review while integrating tools such as GitHub, Slack, Jira, and Confluence. Design scalable pipelines, improve AI quality through evaluation and observability, manage production tradeoffs, and apply security controls to AI applications. Own initiatives from problem definition through production while collaborating with engineering and security stakeholders.

Build and operate AI-native engineering workflows, agentic coding systems, evaluation frameworks, guardrails, and customer-facing AI products. Design distributed systems and LLM pipelines using TypeScript, Go, AWS, and related cloud technologies. Lead architecture, code reviews, reliability practices, and end-to-end project delivery while helping engineering teams adopt AI tools and workflows. Interview candidates, document best practices, and continuously evaluate advances in foundation models and AI development tools.

Build and operate production AI systems for safety-critical enterprise applications. Responsibilities include multi-step LLM pipelines, agent orchestration, graph and hybrid retrieval, evaluation frameworks, observability, model selection, and production incident response. The role requires strong Python, FastAPI, asynchronous services, testing, and experience with LLM deployment, tool-calling workflows, evaluation, retrieval, and production operations. Graph expertise with Neo4j and Cypher is preferred, along with enterprise AI security and Azure experience.

Build and support reliable dashboards for AI infrastructure and financial models, including TCO, tokenomics, and compute capital models. Responsibilities include implementing features, loading model releases, validating data, developing accuracy checks, collaborating with analysts, creating charts and explanations, answering client questions, and contributing to research newsletters. The role requires strong Python or TypeScript skills, software engineering experience, numerical accuracy, and effective use of AI coding agents.

Own platform quality, architecture, security, compliance, technology adoption, and production improvements. Design and ship health report products with scientific product partners. Apply deep expertise in distributed systems, database design, or message-driven architectures, while using AI tools responsibly and reducing platform complexity through migrations, deprecations, or refactoring.

Designs, builds, and operates scalable internal applications, backend services, APIs, integrations, and automated employee workflows. Owns solutions from architecture through deployment and support while improving reliability, observability, performance, and maintainability. Collaborates across engineering, product, design, security, and People Technology teams; provides technical leadership through architecture reviews, code reviews, mentoring, and roadmap contributions. The role also explores AI-powered capabilities to improve employee workflows and engineering productivity.

Build and maintain distributed partner solutions across backend services, batch pipelines, frontends, and infrastructure. Design APIs and third-party integrations, implement Infrastructure as Code, integrate AI development tools, monitor production reliability, troubleshoot issues, and collaborate with product managers, QA, engineers, and external partners. Produce technical documentation, participate in architecture discussions, and contribute to code quality, platform stability, observability, and Agile delivery.

Build and ship end-to-end features for Dover's marketplace and ATS. Propose product ideas, implement designs, launch, iterate in production, and collaborate closely with a small engineering team to move quickly and maintain high quality.

Serve as the technical anchor for Domino’s identity and authorization platform. Design scalable, relationship-based authorization using SpiceDB; guide migration from legacy access checks; build cloud-native identity integrations; improve platform reliability, security, and architecture; and advise engineering teams on authorization, APIs, abstractions, and AI-assisted development practices.

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 scale Supabase Storage across client libraries, CLI, CDN, storage servers, and deployment infrastructure. Responsibilities include improving upload and download performance, asset optimization, edge networking, caching, observability, reliability, APIs, developer tools, and the storage explorer. The role also involves PostgreSQL and distributed-systems performance tuning, infrastructure operations, escalated support resolution, and end-to-end project ownership in an asynchronous, remote, open-source environment.

Interns will design, implement, test, debug, and document robotics software in C++ and Python within a Linux and ROS/ROS2 environment. They will contribute to scoped projects involving autonomy, navigation, perception, hardware integration, testing, or developer infrastructure. The role includes debugging hardware-software issues, code reviews, cross-functional collaboration, project communication, and a final presentation. Interns work full time onsite in Burlingame, California, with mentorship and structured feedback.

Plans, develops, and executes manual and automated software tests across functional, regression, performance, component, and system levels. Authors test plans, procedures, and reports; investigates defects and customer issues; maintains testing documentation and version-controlled procedures; and supports software verification and validation throughout the SDLC. Collaborates with multidisciplinary engineering teams, troubleshoots complex systems, supports customer-site integration testing, and contributes to improved testing standards, tools, and processes. The role may involve laboratory work, technical documentation, and obtaining security clearance.

Develop and maintain scientific software for quantum processor calibration, hardware interfaces, testing, monitoring, and operational infrastructure. Collaborate with scientists and engineers, improve architecture and performance, conduct technical investigations, support the full software lifecycle, and participate in on-call support for quantum processing systems.