Top AWS Jobs in Vancouver

Lead architecture, design, and delivery of enterprise-scale Agentic AI solutions. Oversee multiple engineering pods, mentor teams, manage client-facing architecture discussions, ensure production-grade MLOps, cloud infrastructure, microservices, observability, and adoption of emerging AI technologies.

Build and prototype state-of-the-art large language models and AI assistants, take services from ideation to production, fine-tune open-source models, use LLM platforms, analyze model statistics and projections, and collaborate cross-functionally in a fast-paced hybrid Palo Alto environment.

Build and maintain backend systems and infrastructure for an AI-focused startup. Implement services in Python/TypeScript, design moderately complex systems, manage SQL/NoSQL databases, deploy on public cloud (AWS/GCP/Azure), use containerization and IaC, build CI/CD pipelines, implement monitoring/logging (Prometheus/Grafana/ELK/DataDog), and ensure strong networking, Linux, and database security.

Lead technical partner enablement and co-delivery for LanceDB: onboard and train partner engineers, run PoCs and architecture reviews, author reference architectures and deployment blueprints, relay partner feedback to product, and support GTM and thought-leadership activities to scale partner integrations.

Senior individual contributor owning AI/ML products end-to-end: discover opportunities, define roadmaps, make build-vs-buy decisions, lead vendor evaluations and cross-functional delivery, monitor KPIs and operational signals, and drive continuous improvement and adoption.

The Forward Deployment Engineer will deploy and optimize Generative AI solutions, architect scalable infrastructure, and implement data pipelines across multi-cloud environments while collaborating with cross-functional teams to maximize business value.

Design, build, deploy, and optimize AI/ML models and pipelines (including LLMs and RAG). Integrate models into production, work with cross-functional teams, ensure monitoring and compliance, and contribute to scalable AI systems and automation.

Design, build, and operate scalable, secure cloud infrastructure and CI/CD pipelines. Manage Kubernetes environments, implement IaC (Terraform), improve observability, troubleshoot production issues, support security/compliance, and mentor junior engineers to optimize platform reliability and cost.

Design, build, fine-tune, and deploy production-grade AI and ML systems (LLMs, RAG). Develop scalable APIs, integrate AI into business systems, monitor model performance, and collaborate with cross-functional teams.

The Detection & CorpSec Engineer at Quora will build and maintain detection systems, strengthen corporate security controls, and respond to security incidents while collaborating with IT and advising non-technical teams.

Develop scalable applications and backend infrastructure for brand safety and content suitability. Design APIs, deploy ML models, and manage database systems.

Seeking a Sr DevOps Engineer to design and maintain secure, scalable AWS cloud infrastructure, manage CI/CD pipelines, and improve system reliability across advanced data analytics platforms.

The Principal Software Engineer at Snout will define architectural direction, build features across the stack, and enhance team effectiveness, ensuring quality and performance.

As a Senior Software Engineer, you'll develop and enhance the Snout web platform, collaborate with teams, and lead technical projects while ensuring performance and reliability.

The role involves building and scaling growth engineering products, balancing quality and speed effectively, and influencing product direction and AI-driven growth solutions.

As an ML Engineer at Luma AI, you will design high-performance model serving pipelines, manage GPU resources, and optimize CI/CD for large-scale AI systems.

As a Software Engineer in Reliability, you'll architect and manage multi-cloud GPU infrastructure, ensuring performance, security, and scale while debugging complex hardware/software issues.

Contribute to the reliability and performance of Mithril's GPU orchestration platform through automation, observability, and infrastructure management. Collaborate with the team to ensure scalability across multi-cloud environments while maintaining systems stability and implementing SLOs.

The Frontend Engineer will build web interfaces for a healthcare APIs clearinghouse while collaborating across teams to ensure high-quality, responsive design and functionality.

Design, build, and deploy AI-powered legal applications using LLMs, RAG, and agentic AI. Partner with legal stakeholders to translate workflows, build document ingestion and vector search pipelines, ship production-grade features, implement governance/security controls, and mentor/legal users while aligning solutions with enterprise architecture and monitoring quality and evaluation metrics.

Design, build, and maintain scalable distributed data pipelines and a secure data lakehouse for streaming and batch processing to support real-time analytics, ML, and experimentation. Automate, test, and harden workflows, architect logical and physical data models, build ML model features, and collaborate with product, analytics, and data science teams to turn data into value.

Design and build end-to-end, enterprise-grade systems that enable AI agents to initiate and complete finance workflows. Own features across backend and frontend, integrate AI/ML models into auditable production systems, ensure scale, security, and reliability, and collaborate with product and customers to solve accounting problems.

Design, build, and operate secure, tenant-isolated cloud infrastructure and CI/CD for an AI-native multi-tenant platform. Implement observability, policy-as-code, SLAs, incident response, and automate provisioning (Terraform/Helm). Support deployment, monitoring, and secure operations for ML/agent systems at scale.

Founding full-stack engineer to architect and build a production platform combining large-scale data systems and AI-native agents. Work across backend, frontend, data pipelines, agents, and deployment systems; define architecture, devops, CI/CD, and early engineering processes while shipping features and growing the team.

Operate, maintain and improve the global Tyk Cloud platform: run production Kubernetes clusters, manage cloud infrastructure, automate operations, run on-call incident response, create monitoring and dashboards, conduct post-incident analysis, document SRE processes, and drive reliability, efficiency and multi-region/multi-cloud expansion.