Top AI Jobs in Calgary

This job is for candidates with AI infrastructure experience to submit their resumes for future opportunities. No specific role is posted.

As a Software Engineer in AI Infrastructure, you will design and develop core platform components, build APIs and services, enhance performance, and automate tooling while collaborating across teams and improving system reliability.

Lead development of AI-native production systems: convert AI-assisted prototypes into scalable, secure software; own architecture, reliability, and technical direction; direct and control AI coding agents; define engineering standards and workflows; collaborate with founders on product and strategy; debug complex issues and elevate engineering quality.

Create high-volume, high-quality marketing content using generative AI and AI agents (video, image, social). Develop timely campaign ideas, track AI and cultural trends, experiment with formats, and work closely with founders and the marketing team to shape brand voice and growth.

Design and optimize high-performance kernels and custom operators for attention, MoE, GEMM, quantization and collective communication across NVIDIA, AMD and AWS Trainium. Improve LLM inference runtimes, develop distributed training/inference solutions at scale, use compilers and SDKs (Neuron, Torch Dynamo, PyTorch/XLA), contribute to open-source, and publish technical findings.

Lead delivery of customer-facing AI products, internal AI enablement, and BI/reporting solutions. Manage developers, data scientists, and BI specialists; set architecture, standards, roadmaps, governance, and SDLC best practices; prioritize work, mentor staff, and partner with product and business stakeholders to deliver scalable, secure, and reliable AI and reporting systems.

The AI Solutions Manager leads client engagements focused on AI and automation, managing project lifecycles, optimizing internal processes, and integrating AI tools. They also provide training and performance monitoring.

Build and productionize AI systems for logistics: multi-agent copilots, forecasting/optimization models, evaluation and observability, continuous learning loops, and operational reliability. Mentor engineers and make build-vs-rule tradeoffs while shipping high-impact ML services.

Build and maintain internal AI enablement tools, workflows, and guardrails to help engineers use coding agents and LLMs safely. Evaluate models, partner with teams to apply AI, track adoption and impact, and provide documentation, coaching, and advocacy to increase engineering velocity.

Lead executive interviews, stakeholder workshops, and current-state assessments to identify operational gaps and opportunities. Develop business cases, operating models, governance, KPIs, roadmaps, and practical AI-enabled solutions. Advise on AI strategy, innovation, commercialization, customer experience, and change management. Support transition of recommendations to delivery teams and occasionally participate in business development.

Lead global R&D to define technical strategy and roadmaps, prioritize AI-driven modernization, manage engineering and test teams, oversee AI/ML model validation in regulated clinical environments, own R&D budgeting and vendor partnerships, ensure regulatory compliance, and drive operational excellence and ethical AI adoption to improve clinical trial outcomes.

Build high-performance API services and production-grade Generative AI systems. Design and implement end-to-end RAG pipelines, vector stores, embeddings, and latency-optimized generators. Develop agentic AI using LangChain/CrewAI/Semantic Kernel, integrate LLM APIs and AWS Bedrock, manage CI/CD and ML pipelines, and apply evaluation frameworks to detect hallucinations and optimize performance.

Embed with client engineering teams to deploy, integrate, and scale enterprise generative AI solutions. Build agentic systems, train and serve LLMs with Vertex AI, integrate models with BigQuery/AlloyDB/Spanner, implement streaming inference pipelines, and ensure operational reliability while collaborating with stakeholders to translate business goals into production-grade architectures.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Perform rating and annotation tasks for AI development following project guidelines. Maintain accuracy, meet deadlines, communicate in French-Canadian and English, and complete research within short throughputs. Temporary freelance role, 15–20+ hours/week, remote.

As a Sales Executive, you will hunt for new clients, manage enterprise accounts, and create revenue streams while collaborating with internal teams.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.