Top AI Jobs in Calgary

Build and operate distributed backend services and genomic reasoning engines that combine whole genome bioinformatics with AI. Design scalable data models, retrieval and vector search systems, and deterministic guardrails to ensure scientifically accurate, explainable genomic AI for production use.

Design and build production AI systems and distributed backend services that enable genomic reasoning, retrieval, and data platforms. Integrate genomic annotations and interpretation logic, architect high-performance data models and storage across PostgreSQL, DuckDB, Qdrant, Redis, and Spark. Ensure AI outputs are accurate, explainable, and grounded in genomic evidence while collaborating across engineering and bioinformatics teams.

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.

Ship real open-source integrations and MCP servers to bring SearchApi to agent and automation frameworks. Create PRs, example apps, docs, and integration guides. Stay current with the agent ecosystem, pick high-leverage targets, and work independently to deliver production-ready integrations.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Lead strategy and architecture for GTM and finance systems (Salesforce, NetSuite, Data360/Snowflake, Agentforce). Manage a Salesforce admin, design and operate autonomous Agentforce agents, ensure data governance and a unified customer profile, oversee API integrations and migrations, and build testing and release processes to maintain system integrity and compliance.

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

As an AI Process Forward Deployed Engineer, you will deploy enterprise workflows, improve systems, drive adoption, and collaborate across teams to enhance AI integration in business processes.

The engineer will develop features for an AI workspace platform, deploy AI solutions in public sector environments, and interact with clients.

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.

Create high-quality video content and integrate AI tools into production workflows, combining storytelling and video craft to enhance cinematic quality.

The Senior Product Manager will drive the AI product roadmap for Revenue Cycle Management, overseeing product lifecycle and collaboration with various teams to enhance billing workflows with AI integration.

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

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

The Director of Product Management will lead product strategy for AI solutions in finance, focusing on innovation and collaboration across disciplines while managing customer relationships and rapid prototyping of financial applications.

Translate cutting-edge ML and physics research into production-grade scientific code, architect and scale large simulation and training pipelines on GPU infrastructure, optimize hardware-level performance, support models through full product lifecycle, and integrate complex datasets and ML models into external-facing drug and materials discovery products.

The Machine Learning Engineer will manage the ML lifecycle, develop models, ensure performance, and collaborate with a diverse team to build AI-first products.

The role involves end-to-end machine learning lifecycle management, including data processing, model development, rigorous testing, and production deployment, focusing on large quantitative models for AI-first products.

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

Design, prototype, and ship AI-powered observability features using LLMs and agentic workflows. Rapidly iterate with cross-functional teams to integrate AI into incident detection, triage, and automated analysis. Build scalable, production-ready solutions in cloud-native environments and use observability tooling to troubleshoot and improve system behavior. Own end-to-end delivery and collaborate on product, data, and infra integration.

Design and deliver enterprise-grade AI/GenAI solutions on Salesforce or ServiceNow. Lead RAG pipelines, LLM workflows, NLP automation, and vector retrieval integrations. Architect scalable API/microservice integrations, ensure performance, security, and reliability, and define AI governance and guardrails. Collaborate with product, engineering, and customers through discovery, workshops, and demos to operationalize AI for Field and Customer Service workflows.

Manage early-stage grantmaking for the Transformative AI Fund: evaluate applications, recommend grants, source opportunities, support grantees, build partnerships, represent the fund, and develop systems and LLM-assisted tooling to improve grant processes.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

Work with founders and the founding team to build AI-powered internal tools and automations, run GTM and community activities, and manage daily operations. Own content, events, scheduling, vendor logistics, and process design while using AI tools to automate and ship solutions.