Top AI Jobs in Calgary

Lead the creative development of AI-assisted video content, overseeing multidisciplinary teams, driving innovation, and integrating Generative AI into video production workflows.

Design and build scalable .NET backend services and gRPC microservices; optimize data layers (SQL Server, MongoDB, Elasticsearch); implement cloud integrations on AWS and Azure; ship AI/ML features (LLMs, RAG, vector search, ranking, personalization) and operate MCP servers; contribute to CI/CD, observability, containerization, and production ML integrations impacting high-traffic consumer marketplaces.

As a Principal AI/ML Architect, you will lead ML assessments, provide architectural guidance, and advise on ML operations across diverse client engagements, ensuring technical quality and building customer confidence through high-quality proof of concepts.

The AI/ML Engineering Manager leads ML engineering teams, manages client engagements, shapes architecture, ensures technical quality, and drives business growth through ML operations.

As a Staff AI Software Engineer, you will design and build autonomous AI systems for security testing, focusing on reliability, scaling, and integration with enterprise infrastructure, all while collaborating with top security experts.

Lead AI strategy and execution, implementing customer automation, refining data governance, and driving engagement through AI-driven experiences.

As a Staff Applied AI Engineer at Invoca, you'll architect and deploy AI systems, engineer advanced RAG systems, contribute to AI evaluations, optimize prompts, and ensure scalable and reliable AI model serving.

Lead design and deployment of production-grade AI solutions, build multi-agent systems and cloud-native ML infrastructure, apply rigorous statistical evaluation, implement generative and predictive models, champion MLOps and data pipeline best practices, and collaborate with clients to translate business needs into technical solutions.

You will design and build LLM-powered features, integrate AI capabilities into workflows, and contribute to internal practices at a healthcare-focused company.

Lead AI technical strategy, architect AI systems, set safety standards, mentor engineers, and evaluate AI models at Midi Health, a healthcare-focused company.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

As an AI/ML Architect, you will define architecture for AI solutions, guide teams, mentor, and align initiatives with business goals, focusing on ethical practices.

The Senior Software Engineer, Voice AI will design and implement complex systems for emergency response communications, oversee AI integrations, and provide technical mentorship.

Lead AI product initiatives from concept to production, define architecture, collaborate with product leadership, and improve AI workflows.

The Senior AI Engineer will design, build, and ship AI-powered product features, integrating LLMs and automating workflows to enhance security insights and user experience.

Design and build multi-agent AI systems and RAG pipelines, orchestrate LLMs and embeddings, develop scalable full-stack (Node.js/Next.js) APIs, optimize infra (SQL, AWS/GCP, Docker/K8s), lead technical design-to-deployment, ensure code quality, and implement video content classification and tagging for influencer marketing.

The Principal Business Consultant, AI will lead projects, consult with clients on AI solutions, and improve business processes, ensuring optimal software adoption and utilization.

Rapidly prototype and iterate AI-powered features (LLMs, embeddings, real-time audio, APIs), lead experiments from hypothesis to proof-of-concept, collaborate with product and engineering to translate prototypes into product-aligned solutions, and share learnings and artifacts to accelerate team innovation.

Build and run scalable AI-first GTM automation: design multi-agent architectures, integrate LLM APIs and marketing/CRM platforms, implement CI/CD and observability, and enable partner teams with templates, docs, and training to drive measurable GTM outcomes.

The Senior Software Engineer will develop AI-driven internal tools for automation across Sales, Customer Success, and Marketing, ensuring scalable workflows and system integrations with various platforms.

Design, build, and operate production multi-agent AI systems and automation for Marketing Operations. Integrate LLMs with business systems (BigQuery, CRMs, Slack), implement RAG pipelines, observability, governance, and scalable serverless/containerized services. Partner with GTM teams to deliver measurable automation and self-service tooling.

The role involves developing high-performance AI features for observability, rapid prototyping, and cross-functional collaboration, aimed at improving incident response and system behavior understanding.

Lead Android-first development of growth experiments and features, using AI-native workflows to design, implement, instrument, and analyze A/B tests. Ship performant, reliable Android experiences at scale, mentor teammates, participate in on-call, and codify AI-native engineering playbooks for broader adoption.

Lead end-to-end development of an agentic AI platform powering customer-facing experiences. Define roadmap, design prompt strategies, evaluation frameworks, and guardrails. Partner with engineering and OpenAI to deploy LLMs, voice models, and automation; drive experimentation to improve accuracy, satisfaction, and automation rates.

Lead end-to-end development of Jerry.ai's agentic AI platform and customer experiences. Define roadmap, partner with engineers on prompt strategies, evaluation frameworks, and guardrails. Drive experimentation to improve automation rates, answer quality, and customer satisfaction. Integrate with partners like OpenAI to deploy voice and workflow automation models and establish AI best practices and platform standards across the org.