Top AWS Jobs in Vancouver

The Backend Engineer will build a multi-cloud inference platform and manage distributed systems for AI model deployment while ensuring operational excellence and low toil services.

The role involves designing, developing, and deploying GraphQL APIs, creating user-friendly interfaces, and collaborating within a remote team on web applications for telecommunications.

The Staff Software Architect designs and builds backend systems, drives architectural direction, mentors engineers, and improves application performance, focusing on hands-on coding and technical leadership.

As a Senior Site Reliability Engineer, you will own AWS infrastructure, ensure reliability, and enhance deployment processes, primarily working with Kubernetes and Terraform.

The Staff Software Engineer role involves leading projects, coordinating engineers, improving processes, and representing PayPal to external partners, focusing on cloud and DevOps responsibilities.

The DevOps Engineer will manage AWS and Azure infrastructure, maintain Linux servers, support production troubleshooting, and ensure security and documentation. The role requires strong scripting and database management skills.

As a Lead Test Engineer, you will design test strategies, implement automation, evaluate user experience, and ensure overall feature quality while collaborating with cross-functional teams.

Join a cross-functional engineering team to build backend tools, APIs and integrations. Lead team-scoped projects, design and operationalize agentic/automation workflows, improve platform reliability and scalability, mentor engineers, participate in code reviews, and ensure results via verification loops and CI/CD practices.

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.

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.

In this role, you will lead frontend architecture and development, ensuring scalability and performance, while mentoring engineers and collaborating across teams to enhance user experiences with modern technologies.

Design, build, and maintain automation and testing infrastructure for the North platform: CI/CD pipelines, GitHub workflows, containerized test environments (Docker/Kubernetes), Helm and ArgoCD deployments, infrastructure-as-code, benchmarking, parallel test execution, and cross-team standards to improve test coverage, reliability, and deployment confidence.

Develop, test, and maintain mobile applications for iOS and Android; collaborate with teams, manage app releases, and ensure high performance.

As a Full Stack Software Engineer, you will develop and deliver full stack features for AI agents integrated into HR and financial workflows, collaborating within a cross-functional team to ensure quality and performance from development to production.

As a Fullstack Software Engineer, you'll collaborate with multi-functional teams to enhance AI-driven solutions, participate in software development best practices, and take ownership of various platform functional areas.

As a Fullstack Software Engineer, you'll enhance Evisort's AI-driven contract management platform by collaborating with cross-functional teams and taking ownership of multiple functional areas from development to production.

Lead design and implementation of a zero-to-one, real-time collaborative web content platform. Own architecture, build backend sync and delivery services, craft low-latency frontend editing experiences, define engineering standards, evaluate third-party tradeoffs, and mentor engineers while partnering with product and design.

Design, implement, and scale event-driven, distributed backend systems in Python on AWS to process and enrich large-scale document and media datasets. Lead technical projects, mentor engineers, integrate ML/LLM components, optimize performance, maintain observability, and collaborate with Data Science, ML Engineering, and Product to deliver reliable high-throughput content processing services.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Lead technical direction and architecture for the Fable backend, own platform reliability (databases, CI/CD, queues, observability), run incident response and postmortems, mentor engineers, collaborate cross-functionally with product/design/ML, and build platform capabilities enabling faster, safer delivery.

Lead AI engineering on the Data Platform: build Databricks Apps deployment paths, construct an AI layer over the Medallion Architecture and semantic layer, enable LLM/NLP systems and agentic workflows, embed AI tooling in the developer lifecycle, enforce guardrails for production safety, define metadata/modeling patterns, and mentor engineers to accelerate AI adoption.

Lead and grow a software engineering team building enterprise contract-management AI products. Partner with product, ML, and design to deliver scalable SaaS solutions, own platform performance and operations, recruit and mentor engineers, and drive AI initiatives (LLMs, agents, RAG) with strong devops, testing, and observability practices.

Design, build, and optimize scalable AI-enabled application features and services. Integrate ML models and generative AI, ensure secure and test-driven implementations, troubleshoot AI performance, mentor engineers, and drive AI architecture, CI/CD, and best practices across teams.

Act as the technical lead in sales, running discovery workshops, designing Databricks Lakehouse architectures, building demos/POCs, responding to RFPs, advising on integrations with AWS/Azure/GCP, collaborating with data scientists on ML/GenAI demos, and enabling internal teams. Travel ~40%.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.