Top AWS Jobs in Calgary

The Databricks Solution Architect will design and implement data architectures, serve as pre-sales engineering support, and mentor on Databricks capabilities, ensuring the delivery of scalable solutions aligned with customer needs.

Lead and mentor a team of Forward Deployed Engineers to deploy Cohere's North platform into private cloud and on-premises environments. Own technical delivery and customer success, collaborate with Product/Engineering/Sales, optimize K8s services (OpenSearch, databases), define GPU/CPU scaling, and build scalable processes and tooling.

As a Staff Backend Engineer, you will design and own system architectures, lead feature delivery, mentor engineers, and improve system performance and security.

Lead architecture and implementation of high-throughput, low-latency AdServer and Exchange services. Design scalable, resilient distributed systems, integrate demand/supply partners, improve RTB/auction capabilities, advance observability and automation (including AI-driven testing/IaC), and mentor engineers to increase platform reliability and revenue growth.

Design, develop, and maintain Salesforce CRM and CPQ solutions including Apex, LWC, Flows, and integrations. Support quote-to-cash workflows, Zuora integrations, code reviews, testing, deployments, production troubleshooting, and technical documentation in a cross-functional agile team.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

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.

Build and scale the enterprise sales organization: define sales architecture, hire and lead founding sales team, own enterprise ARR growth, close initial six- and seven-figure deals, establish land-and-expand motions, manage channel/partner strategy, navigate enterprise security/procurement, and align sales with product and engineering.

Lead end-to-end delivery of large-scale analytics and data management programs: enforce delivery best practices, manage multi-workstream teams, liaise with senior stakeholders, ensure quality/performance on cloud data platforms, and drive account growth and talent development.

Drive partner success by guiding GTM strategy execution, building long-term partner relationships, implementing Tackle's operating model, enabling co-sell and marketplace best practices across AWS, Azure, and Google Cloud, improving workflows, using data to measure outcomes, and communicating results to stakeholders.

Lead design and operations of GPU infrastructure and Kubernetes-based AI platform environments. Manage capacity planning, optimize training/inference workloads, define reliability and security practices, implement IaC, monitoring, and disaster recovery, and collaborate with AI engineering to evolve infrastructure.

Senior backend engineer responsible for building and scaling microservice-based backend systems, driving technical initiatives, collaborating with product and sales, prioritizing customer needs, improving infrastructure and performance, and using AI tools to accelerate development and workflows.

The Cloud Software Engineer will design distributed systems for observability, ensuring reliability and performance, while automating operational work and collaborating with teams.

The Business Solution Architect leads the design and delivery of telecom solutions, bridging business needs and technical implementation while supporting digital transformation initiatives and guiding teams on architecture and integration.

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.

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.

The Senior Machine Learning Engineer will lead machine learning infrastructure improvements, mentor engineers, and ensure model deployment and optimization standards are met. Responsibilities include architecting ML pipelines and engaging with stakeholders on tech solutions.

Lead and mentor engineering teams to deliver high-quality, AI-driven software, ensuring accountability and continuous improvement in development processes.

The role involves leading full-stack architecture decisions, building scalable systems, optimizing performance, and mentoring developers, while driving platform strategies.

Own cloud operational health, architecture intelligence, and cost optimization. Analyze cloud spend, build dashboards/reporting, enforce governance, review architecture for cost impact, and translate technical findings for engineering, finance, and executives.

The Principal Application Scientist at Dotmatics will provide technical leadership and consult customers on SaaS solutions, focusing on data integration and architecture in scientific environments.

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.

Lead AI strategy engagements, manage complex client relationships, drive discovery, and deliver actionable plans to increase business effectiveness with AI solutions.

Lead the design and delivery of SaaS products powered by data, ML, and AI, collaborating across backend, systems, and cloud infrastructure. Drive architecture evolution, ensure operability and performance, and mentor engineering teams.