Top Azure Jobs in Calgary

Principal IC responsible for reliability, observability, and modernization of a .NET-based Platform Services portfolio on Azure. Own architecture, resilience patterns, shared libraries, and migration of legacy .NET services. Implement observability, event-driven messaging, and AI-first engineering practices while mentoring engineers and partnering with architecture teams.

Technical lead for a scrum team building reporting/BI capabilities for the CEM platform. Hands-on work in SQL/Oracle and BI tooling, sprint leadership, query performance tuning, AI-first tooling adoption, people management for 4–5 engineers, client-facing requirements gathering, and cross-team collaboration to ensure high-quality, performant reporting solutions.

Lead QA & Standards for an enterprise SaaS platform, owning manual QA, automation, and performance testing. Set org-wide test standards, define release quality gates, drive AI-first QA adoption, grow performance engineering, manage distributed teams, and partner with engineering leadership on automation strategy and quality transformation.

Lead technical ownership and hands-on engineering for the integration backbone of a financial SaaS platform. Modernize legacy integration processes into .NET services, design reliable REST and file-based connectors, optimize Oracle SQL/PL/SQL, improve observability, and drive cloud-native Azure patterns. Mentor engineers, enforce standards, and champion AI-first development to increase delivery velocity and operational quality across multiple production ecosystems.

Lead a small scrum team as hands-on technical authority, writing and reviewing full-stack C#/.NET, Angular, and Oracle code; run sprint ceremonies; drive AI-first tooling adoption; manage and develop 4–5 engineers; coordinate cross-functional delivery and client engagement.

Manage two Reporting/BI scrum teams delivering financial reporting for the CEM platform. Own delivery, people, and client relationships; provide technical SQL/BI leadership; drive AI-first tooling adoption; coordinate cross-functional alignment; hire and develop engineers across distributed locations.

Lead a small scrum team as the daily technical authority: write and review full-stack C#/.NET and Angular code, run scrum ceremonies, set priorities, unblock engineers, enforce quality standards, drive AI-first tooling adoption, manage 4–5 engineers, engage client stakeholders, and coordinate cross-team delivery and release readiness.

Design and implement end-to-end AI systems and production-grade components. Build and maintain RAG pipelines, backend services, APIs, and data pipelines. Write Python code using Azure AI SDK. Implement document digitization, vectorization, semantic search, and content summarization. Prepare training/evaluation datasets, participate in code reviews, and drive engineering quality and deployment of AI-powered SaaS workflows.

Lead identification and remediation of revenue leaks across US Commercial and Government contracting. Optimize Medicaid claim validation and expand controls for 340B duplicate discounts, MDP, and MFN compliance. Gather and synthesize requirements, evaluate Model N Validata vs custom builds, and coordinate cross-functional technical implementation.

Build and prototype state-of-the-art large language model systems and deep AI assistants, take services from ideation to production, fine-tune and compare open-source and commercial LLMs, use cloud platforms, analyze model and projection accuracy, and collaborate cross-functionally.

Design, build, and operate backend systems and infrastructure. Work on system design, databases (SQL/NoSQL), cloud platforms, containerization, IaC, CI/CD, monitoring/logging, networking, security, and Linux fundamentals in a fast-paced startup environment.

Design and evolve systems for Motion's infrastructure, focusing on reliable and secure operations across APIs, Linux systems, and cloud environments with a focus on hands-on coding and engineering judgment.

As a Customer Support Developer at Airbyte, you will troubleshoot database issues, support customer integrations, develop database connectors, and collaborate cross-functionally to enhance database reliability and performance.

Lead the deployment of North in private cloud environments, collaborating with IT teams, designing strategies, and resolving technical issues.

Lead the deployment of AI solutions for public sector clients, ensuring compliance with security standards while integrating AI into enterprise workflows.

Design, build, and maintain scalable AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists and engineers to implement and optimize AI solutions, troubleshoot pipeline issues, document best practices, and develop MVP code to transition into production-ready systems.

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.

Design, build, and operate core backend services for an AI-native context management system: ingestion, indexing, retrieval APIs, multi-tenant SaaS features, and agent-facing integrations. Define architecture, ensure observability, iterate from prototype to production, and collaborate across product and infrastructure while owning service reliability and technical direction.

The role involves monitoring and managing SAP systems, HANA databases, performing upgrades, troubleshooting, and ensuring system performance in an Azure environment.

As the DevOps Guardian, you will oversee build, release, and environment management in Azure, collaborating closely with the product team and implementing best practices for continuous delivery.

The Lead Knowledge Engineer develops ontologies, knowledge graphs, and semantic artefacts, influencing data strategies and providing leadership for complex data integration projects.

Design, build, and operate scalable infrastructure and delivery pipelines for a product suite. Lead containerization (Docker, Kubernetes), multi-cloud deployments (AWS/GCP/Azure), CI/CD best practices, and incident-driven improvements. Mentor teams, act as escalation for operations, participate in weekend support rotations, and drive reliability, security, and automation.

The AI Architect will design enterprise-grade AI solutions using Generative AI, LLMs, and orchestration frameworks, focusing on building scalable systems and developing production-ready applications.

Lead QA for an Agentic AI platform: define and execute testing strategy, implement automation, validate LLM outputs and conversational workflows, oversee functional/integration/regression/performance testing, integrate CI/CD, mentor QA engineers, and promote quality best practices across teams.

Design and develop full-stack features, focusing on backend systems with some frontend work, while modernizing applications and integrating AI tools.