Top AWS Jobs in Calgary

The Information Systems Engineer will design integrations and enhance engineering processes across various business systems, focusing on scalability and efficiency. Responsibilities include collaborating with teams to implement systems solutions, optimizing integrations, monitoring performance, and supporting production applications.

Leads enterprise architecture strategy for AI, data platforms, analytics, and governance. Designs scalable lakehouse, AI/ML, streaming, integration, BI, and data governance solutions using cloud technologies. Establishes architecture standards, leads reviews and transformation initiatives, guides build-versus-buy decisions, and ensures security and compliance alignment. Partners with executives and cross-functional technology teams, mentors architects, and drives standardization, innovation, performance, and solution quality across AI and data ecosystems.

Build and operate full-stack product experiences using React, TypeScript, Node.js, GraphQL, PostgreSQL, and related technologies. Own projects from discovery through launch and iteration, design scalable systems, improve performance and reliability, use AI-native development tools, collaborate cross-functionally, participate in on-call, and mentor engineers. The role is based in the Haeundae, Busan office Tuesday through Friday, with remote work on Mondays.

Senior QA/Test Engineer responsible for testing Amazon Connect and contact center technologies, including contact flows, routing, IVR, AI agents, web applications, APIs, and serverless AWS backends. The role develops manual and automated test suites, validates migrations and production cutovers, verifies monitoring and security controls, supports incident triage and UAT, partners with engineers on quality practices, and mentors junior QA engineers.

Build and maintain Safari AI’s cloud infrastructure, including production services, system design, reliability, documentation, and security compliance. The role sets technical direction for the cloud stack, collaborates with engineering and operations teams, improves development processes, and delivers incremental features. Candidates should have 4–6 years of software engineering experience, public cloud expertise, and experience taking complex services from concept through production. Streaming processing and machine learning experience are advantageous.

Build, launch, and maintain gameplay features for Driving Empire on Roblox. Responsibilities include writing performant Roblox Lua code, designing scalable systems, translating product requirements into technical tasks, collaborating with designers and artists, monitoring live features, improving reliability and workflows, participating in code reviews, and playtesting to improve player experience.

Owns end-to-end data infrastructure, including secure data lakes, streaming applications, data warehouse systems, replication and change data capture pipelines. Responsibilities include architecture, deployment, maintenance, performance optimization, security controls, documentation, operational runbooks, and cross-functional partnership with analytics and product teams. The role requires strategic data infrastructure thinking and production experience in SaaS or data-heavy environments.

Staff Software Engineer responsible for setting technical direction, leading complex initiatives, partnering with product and design, mentoring engineers, and owning reliability, performance, observability, and on-call operations. The role spans backend data models and asynchronous processing through frontend design systems and visualizations. Required experience includes 10+ years of full-stack software development, Ruby, PostgreSQL, React, TypeScript, scalable relational systems, and AI-assisted development practices.

Build and improve MongoDB’s distributed networking and observability systems. Responsibilities include enhancing networking performance, availability, scalability, resource efficiency, and low-overhead observability; leading medium-sized projects from technical design through delivery; collaborating across the project lifecycle; contributing production C++ code; and participating in code reviews and feature design.

Build and operate reliable backend services for a developer-focused email platform. Responsibilities include owning features end-to-end, designing APIs and relational data models, scaling databases, building distributed systems with queues and background workers, managing AWS infrastructure, improving observability and deployments, participating in on-call, and partnering with customers and support to improve the product.

The Backend Engineer will build and maintain Resend's email transport infrastructure, focusing on SMTP delivery, routing, and system design for high-volume email sending. They will ensure the reliability and observability of the systems while participating in incident response.

Lead the architecture and evolution of scalable ETL and data-processing systems for customer product catalogs. Design reliable distributed systems, improve throughput and latency, strengthen fault tolerance and observability, and guide technical direction across teams. Mentor senior engineers, conduct architecture reviews, lead cross-functional initiatives, influence hiring and onboarding, and help shape the engineering organization’s long-term technical vision.

Lead architecture and development of secure, high-scale Python and FastAPI payment infrastructure for AI-agent transactions. Design APIs for tokenization, mandates, authentication, attestation, and cryptogram workflows; own security, reliability, observability, testing, Kubernetes provisioning, and production operations. Drive technical initiatives, design reviews, and cross-functional collaboration with product, security, infrastructure, platform, and card-network partners while applying AI-assisted engineering practices.

The Site Reliability Engineer will manage cloud infrastructure, automate tasks, collaborate in agile teams, and ensure service reliability and quality.

Lead design and delivery of scalable ML systems across the full lifecycle for recommendations, forecasting, targeting, and personalization. Collaborate with engineers and product teams, set modeling and productionization standards, mentor data scientists, guide architecture and experimentation, and apply cloud and MLOps best practices to drive measurable product and business impact.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Conduct third-party security assessments, evaluate vendor controls, document risk findings, automate GRC workflows with Python and agentic coding tools, maintain integrations across ticketing and risk platforms, and develop dashboards and reporting. Partner with Procurement, Legal, Engineering, IT, Compliance, and Privacy to support risk-informed decisions and mature security governance processes.

Leads data engineering consulting engagements, serving as a subject matter expert and data architect. Designs scalable data environments, models, pipelines, integrations, warehouses, and visualizations while ensuring quality and governance. Leads architectural decisions, project delivery, technology strategy, and AI-augmented development practices. Mentors technical teams, collaborates with data scientists, analysts, clients, and stakeholders, and drives process improvements and innovation. The remote role may require infrequent travel to the United States.

Leads Affirm’s Resilience Engineering team, defining strategy and managing engineers who build platforms for safe production load testing and chaos engineering. Owns fault-injection and experimentation systems, safeguards, observability, rollback mechanisms, monitoring, and incident response practices. Partners cross-functionally to identify systemic weaknesses, improve reliability, and embed resilience validation into engineering workflows. Requires leadership experience in reliability, infrastructure, or distributed systems and hands-on expertise with production testing, chaos engineering, cloud-native environments, and distributed-system failure modes.

Design, build, operate, and maintain critical distributed systems powering Grafana Cloud Metrics and the open-source Mimir project. Drive projects from concept through production, improve reliability and performance, contribute to roadmap and design decisions, review code, support teammates, manage releases, and participate in follow-the-sun on-call rotations. Work with cloud infrastructure, microservices, observability systems, and large-scale telemetry databases while collaborating in a remote, open-source environment.

Lead approximately 15 engineers and three engineering managers across communications products including SMS, secure messaging, email, and fax. Drive zero-to-one product development, reliability, and deliverability at scale while partnering with Product and Design. Develop engineering leaders, advocate for technical investments, translate technical impact for stakeholders, and guide practical AI adoption in a regulated SaaS environment.

Own end-to-end enterprise deployments of Spellbook’s AI-powered legal technology. Build integrations with document management, identity, and internal systems; design workflow-heavy solutions involving permissions, approvals, routing, and auditability; customize AI workflows; collaborate directly with legal teams and end users; and convert deployment insights into scalable platform features.

Own post-sales technical relationships for Azure-focused customers, providing FinOps guidance, cloud commitment optimization, governance advice, and executive-level business insights. Monitor Azure commitment utilization, lead Quarterly Business Reviews, identify expansion opportunities, and collaborate with Product, Engineering, and Support to resolve challenges and influence the roadmap. The role requires strong Azure expertise, cloud economics knowledge, customer-facing communication, and the ability to translate technical findings into measurable business outcomes.

Own post-sales technical relationships for enterprise and mid-market customers, advising on multi-cloud FinOps, commitment strategy, cloud cost optimization, governance, and savings. Lead executive business reviews, translate cloud consumption data into business insights, identify expansion opportunities, resolve customer challenges with internal teams, and mentor junior Technical Account Managers.

Build and optimize backend services, APIs, databases, and high-performance compute models. Develop systems in C# and Java and optimized C++ simulation code using concurrency, synchronization, multiprocessing, and numerical methods. Design IPC mechanisms, profile performance-critical workloads, contribute to architecture and code reviews, mentor engineers, and support testing and CI/CD. Preferred experience includes parallel computing, scientific or geospatial modeling, cloud infrastructure, containers, observability, and high-throughput pipelines.