Top AWS Jobs in Vancouver

The DevOps Engineer will design, build, and enhance cloud and automation platforms, collaborating with development teams to implement secure and scalable DevOps solutions.

Lead FedRAMP Moderate compliance program from gap assessment through remediation and continuous monitoring. Coordinate Engineering, DevSecOps, Security, and Compliance to implement NIST 800-53 controls, maintain SSPs and POA&Ms, work with 3PAOs and federal sponsors, and align cloud architecture and security controls across AWS/Azure/GCP. Drive documentation, vulnerability management, incident response, stakeholder reporting, and governance.

Co-op AI intern will design, build, test, and improve agentic AI systems, RAG pipelines, and LLM-powered applications. Responsibilities include integration of models and services, evaluation-driven development, observability and governance, troubleshooting performance, and collaborating to turn prototypes into production-ready solutions with strong software engineering practices.

Design, build, and scale highly available AWS cloud infrastructure and Kubernetes (EKS). Implement Infrastructure as Code, CI/CD, monitoring (Prometheus), and security practices. Mentor team members, automate deployments, troubleshoot production issues, participate in on-call rotations, and develop tooling in Go/Python/Rust/Bash to improve reliability and performance.

Lead design and implementation of scalable, secure Forma Data cloud services. Act as technical lead across full software lifecycle, write and operate cloud services, mentor engineers, solve complex distributed-system problems, and collaborate globally to integrate SaaS products with Autodesk tools.

Join the CER team to deploy, operate, manage, optimize, and monitor CER services. Design and execute test strategies, build automated test frameworks and cases, track defects, perform root cause and risk analysis, collaborate with developers/DevOps/product designers, and propose cloud-related reliability and performance improvements.

Lead end-to-end delivery of data and analytics programs, partnering with Data Engineering, Analytics, and business stakeholders to define scope, metrics, and technical plans. Manage dependencies, risks, and trade-offs; communicate status to leadership; improve processes, documentation, and embed data governance, quality, and scalability across initiatives.

Lead full‑stack architecture and technical vision for enterprise systems while architecting and orchestrating agentic, AI-native delivery. Design APIs, services, data pipelines, cloud infrastructure, and integrations with LLMs, RAG, vector stores, and composable platforms. Mentor engineers, drive spec-driven agent workflows, and collaborate with cross-functional stakeholders to deliver production-ready, scalable solutions.

Lead and evolve a cloud-native platform by improving CI/CD, IaC, reliability, security, and automation. Architect scalable hosting, drive DevOps best practices, manage AWS-based infrastructure, participate in on-call and incident response, and mentor cross-functional teams to increase platform resilience and delivery velocity.

Lead and coach multiple micro-sized full‑stack engineering squads, manage capacity and delivery, partner with product and staff engineers on sprint execution, leverage AI tools to accelerate onboarding, ensure operational health, and drive pragmatic, adaptable engineering processes to deliver business outcomes.

Design and build core ML systems for production-grade AI agents, owning model, agent logic, orchestration, deployment, monitoring, and continuous improvement. Implement RAG pipelines, workflow orchestration, evaluation and feedback loops, and ensure scalable, observable, explainable, enterprise-ready solutions in collaboration with product, software, and data teams.

As a Sr. System Administrator, you'll manage hardware and cloud infrastructures, oversee server administration, capacity planning, and automation initiatives while collaborating across teams for project implementations and system security.

Manage global software engineering teams, oversee development, drive product innovation, and promote best practices in a cloud-based environment.

The Senior Software Engineer will design and develop solutions for asset discovery and integrate with cloud services, focusing on scalability and collaboration within teams.

Build and prototype polished, high-fidelity customer-facing web components and UX platforms; iterate based on user and stakeholder feedback; use data to drive improvements; create wireframes and experiments; integrate with backend services via REST/GraphQL and ensure designs scale.

The DevOps Engineer will design and maintain cloud infrastructure, implement CI/CD pipelines, automate processes, and ensure security and observability for reliable systems.

Oversee IT systems supporting drug discovery, modernize infrastructure, mentor team members, and lead technical projects in both cloud and on-prem environments.

The Systems Administrator will manage cloud and on-prem infrastructure, troubleshoot issues, support internal tools, and automate operations to improve efficiency.

As a Senior Software Engineer, you'll lead the design and reliability of data systems that link ad visibility to customer purchases, focusing on big data engineering and backend service optimization using C#, ClickHouse, and SQL.

The Solutions Architect will design and deliver cloud-based solutions for insurance clients, collaborating with them to meet requirements and ensuring implementation aligns with expectations.

Own and evolve Babylist's AWS infrastructure, Terraform IaC, Kubernetes/EKS clusters, CI/CD, and observability for a platform serving millions. Lead incident response, improve developer tooling, and set reliability standards across engineering teams.

Design, build, and scale Snowflake ingestion pipelines and ML/LLM systems. Create agentic tooling to generate, test, and maintain pipelines. Collaborate with analysts, data scientists, and product teams to deliver reliable, high-performance data infrastructure and operationalize models for an AI-first e-commerce platform.

The Staff Software Engineer, Backend for Capacity Modeling develops scalable backend systems, maintains capacity models, and collaborates on technical strategies while ensuring system availability and high-quality code delivery.

Build and maintain backend systems for money movement and card ledger features. Design, develop, and launch scalable APIs and services (Python or Kotlin) using AWS, MySQL, and Kubernetes. Collaborate with product, design, data science, and cross-functional teams, support operations and on-call, create and monitor metrics, participate in code reviews and hiring, and deliver well-tested, extensible solutions.

Design and build production-grade ML systems and LLM-powered agent frameworks (RAG, orchestration, evaluation). Own model lifecycle from data strategy to deployment, monitoring, and continuous improvement, partnering with software engineers, product managers, and data scientists to integrate scalable, observable, and enterprise-ready agents.