Top AWS Jobs in Vancouver

Develop and maintain enterprise software applications, focusing on back-end development, API development, and ensuring application security while contributing to software improvement processes.

The Software Engineer will design and implement systems across the stack, focusing on AI-native engineering principles, distributed systems, and high-performance data processing.

As a Software Development Manager, you will lead a senior engineering team to develop platform capabilities, drive modern practices, and enhance developer productivity while ensuring compliance.

The Account Manager will nurture customer relationships, manage support escalations, negotiate commitments, identify growth opportunities, and deliver quarterly reviews, ensuring high customer satisfaction and alignment with cloud vendor goals.

Design and advance core infrastructure for engineering, ensure Kubernetes reliability, automate operations, and support AI infrastructure.

The Senior Staff SRE leads reliability engineering initiatives, drives operational excellence, mentors staff, and influences architecture to enhance system reliability and performance.

Build and own adaptive phishing simulations and real-time behavioral ingestion systems using LLMs. Design interfaces for security teams, ship full‑stack, scalable code, work with early customers, and make foundational architectural decisions.

Senior individual contributor who architects, prototypes, and ships production-grade AI solutions for Finance. Focus areas include agentic AI, multi-agent orchestration, ML forecasting and anomaly detection, RAG and vector-store solutions, responsible AI and governance, and embedding AI into FP&A processes. Partners with engineering, IT, security, and finance teams to productionize systems and establish standards, monitoring, and controls.

Designs and executes testing and measurement for retail and brand partners: data extraction, modeling, attribution/incrementality analysis, BI visualization, and delivering actionable insights. Mentors junior analysts and collaborates cross-functionally to define data requirements and improve measurement practices.

Design, build, and operate shared, reusable platform infrastructure and services (Kubernetes, CI/CD, messaging, databases, service mesh) across multi-cloud, multi-region environments. Develop automation, observability, and APIs; support internal teams and participate in on-call rotations to ensure reliability, scalability, and performance.

Build and own a versioned, documented gold data layer from lakehouse silver tables for AI research. Transform, validate, and productize multi-modal datasets and pipelines (Databricks/PySpark) to support model development, evaluation, and production ML/LLM workflows while ensuring data quality, provenance, and regulatory controls.

Own and operate the production cloud (SaaS) environment, design and automate infrastructure (IaC), implement monitoring/observability, leverage AI tools to improve operations, support on-call incident response, diagnose production issues, mentor engineers, influence architecture, and drive CI/CD and performance optimization.

Design, build, and operate production-grade generative and agentic AI applications and services. Develop Python backend services, RAG pipelines, multi-agent systems, LLM integrations, APIs, and cloud deployments. Implement observability, security, and engineering best practices while mentoring junior engineers and driving platform architecture decisions from prototype to production.

Lead the design and implementation of a unified observability platform, focusing on architecting observability pipelines and implementing tools like Prometheus and Grafana on AWS.

Lead and grow a platform engineering team focused on Infrastructure, SRE, and DevOps. Set technical direction, deliver platform roadmaps, oversee cloud infrastructure and deployment pipelines, build AI-powered internal tools, improve developer experience, own incident management and on-call sustainability, and collaborate with product, security, and compliance to ensure secure, scalable, observable systems.

Partner with Account Executives to drive Commercial new business by leading technical discovery, solution architecture, demos, and POCs; guide complex multi-stakeholder deals; provide product and GTM feedback; and build scalable enablement resources, demo environments, and solution blueprints for the SE team.

Build and maintain internal engineering services and automation to support product teams. Improve observability, CI/CD, infrastructure as code, and cloud-managed services. Own running services, participate in incident response, collaborate cross-functionally, and drive reliability, scalability, and efficiency improvements.

Build and maintain platform services for user lifecycle and HRIS integrations that process millions of records. Design, implement, and operate scalable, reliable microservices, APIs, and event-driven systems using cloud and container technologies. Contribute to design and code reviews, troubleshooting, migration from monoliths, estimation, and mentoring junior engineers.

Lead design, build, and maintenance of User Domain and HRIS integration services handling millions of user records. Architect scalable, secure microservices, mentor engineers, own features end-to-end, collaborate cross-functionally, and improve performance, reliability, and tooling.

Lead architecture and delivery of enterprise web and cloud-native solutions using React, Node.js, and AWS Serverless. Define platform strategy, enforce standards, design CI/CD, mentor engineers, and drive large cross-functional projects ensuring scalability, security, and performance.

Design, train, evaluate, and deploy predictive transportation and delivery ML models (primarily XGBoost). Perform EDA, feature engineering, experiment design, and statistical evaluation. Build production ML pipelines and MLOps practices on Google Vertex AI. Collaborate with data engineering and supply chain stakeholders to translate operational needs into scalable solutions.

Lead advanced analytics and ML projects: perform EDA, feature engineering, statistical modeling, and build/optimize production ML and Generative AI solutions (LLMs, embeddings, RAG). Collaborate with engineering and MLOps to deploy and monitor models, create visualizations and dashboards, translate insights for stakeholders, and mentor junior team members.

Own and ship end-to-end full-stack features for a high-scale, AI-native publishing marketplace. Design APIs, optimize queries, deploy cloud-native apps, build LLM-powered capabilities, ensure security and privacy compliance, mentor engineers, influence architecture, and maintain reliability and performance under load.

Design, build, and operate global cloud infrastructure for a containerized SaaS platform. Lead end-to-end infrastructure projects, improve automation and observability, define SLOs/SLIs, participate in on-call rotation, mentor engineers, and support cross-functional teams with technical issues.

Lead design and implementation of test automation frameworks, architect AI-driven and self-healing testing ecosystems, build automation for web SaaS services, mentor SDETs, prototype agentic tooling, and collaborate across platform and product teams to improve reliability, scalability, and delivery velocity.