Top AWS Jobs in Calgary

As a Full Stack Engineer, you will develop frontend and backend features, write robust code, and collaborate with team members to meet project requirements.

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.

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 Backend Engineer at Trust Wallet, you'll develop backend features for multiple platforms, maintain infrastructure, ensure system monitoring, and foster team growth.

Build and scale the internal developer platform: create tools, services and automation (CI/CD, canaries, feature flags, access workflows) using IaC (Pulumi/Python) and Kubernetes to enable safe, fast shipping. Drive platform initiatives, mentor teams, lead AI tool adoption for engineering, participate in on-call and design/code reviews, and ship major improvements across the organization.

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

Lead and manage AI teams to design, train, deploy, and operate production-grade ML and generative AI systems for security detection and response. Define AI roadmap, partner with product and platform teams, uphold secure MLOps practices, mentor staff, recruit talent, and deliver scalable, observable AI integrated into production cloud environments.

Lead design and implementation of scalable APIs and agent communication layers for an AI-agent driven advertising marketplace. Build high-throughput backend systems, integrate agent frameworks and adtech partners, drive architecture for authentication and protocols, mentor engineers, and prototype agent communication patterns while collaborating with product and design.

Use diverse data sources to evaluate product performance, build automated ETL/data workflows, design dashboards and KPIs, own data product quality, and provide analytical insights to guide product and business decisions while establishing monitoring frameworks and best practices.

Lead technical pre-sales strategy and advanced product demonstrations for enterprise cybersecurity and cloud customers. Mentor SEs, design solution architectures, shape POCs and product feedback, drive process improvements, and support executive-level customer engagements to close strategic deals.

Lead design and rewrites to build a scalable, resilient backend and cloud infrastructure. Own data storage performance, CI/CD pipelines, IaC, observability, incident response, and analytics. Mentor engineers, support customer onboarding and integrations, and drive reliability and scalability for AI-first products.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

Lead architecture and rewrites for a scalable, resilient AI-first platform. Own backend systems, data storage performance, deployment pipelines, cloud infrastructure via IaC, observability, incident response, and analytics. Mentor engineers and enable rapid customer onboarding and AI-driven automation.

Design, architect, and implement new features for the Spellbook application while collaborating with product management and improving existing functionalities using AI technologies.

The role requires designing and developing web applications and backend systems, integrating LLMs, and ensuring quality software delivery.

Lead the architecture and development of enterprise software tools, focusing on secure cloud systems, Node.js applications, and AI integrations while ensuring quality and reliability.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The Founding Software Engineer will build and enhance crisis-intervention software, focusing on mobile and web applications for government welfare, ensuring compliance and integrating data securely. Responsibilities include feature development, security enhancements, and managing interns.

As a Founding Engineer, you'll develop backend systems, optimize applications, and influence technical direction for an AI-powered knowledge platform.

The Full-Stack Engineer will develop and maintain web applications, translating UI/UX designs into responsive apps, optimizing applications, and writing clean code.

The Technical Architect is responsible for designing and implementing scalable solutions, engaging with customers and vendors, and mentoring engineering teams. They must contribute code and ensure successful delivery while maintaining a hands-on approach.

As a Data Engineering Architect, lead the transformation of data engineering into a modern platform, oversee architecture and technical leadership, design scalable systems, ensure data quality and governance, and mentor teams for a data-driven culture.

The role involves designing and maintaining reinforcement learning environments, developing containerized execution environments, managing integrations, and collaborating with data operations for AI training.

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.