Top AI Jobs in Calgary

Conduct research on AI accelerator architectures and semiconductor supply chains to assess power, cooling, and infrastructure implications. Monitor data-center build-outs and industry disclosures, synthesize findings into written briefs and competitive-intelligence products, and ground analysis using Enverus energy datasets.

Conduct primary and secondary research on power demand from data centers, monitor regulatory filings and interconnection queues, build and audit financial Excel models, synthesize findings into concise briefs and data tables, support senior analysts on large projects, and use Enverus proprietary datasets (PRISM) to ground research.

Build, deploy, and maintain AI-powered agents, APIs, and applications for People operations on Snowflake. Integrate Workday/Notion, ensure security and data governance, design multi-model LLM reliability, and own production lifecycle including CI/CD, monitoring, and incident response while working with non-technical stakeholders.

As an AI Engineer, you will develop and maintain data pipelines, manage data integration, and enhance data quality for analytics projects.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Lead end-to-end product design across web and native, run user research, build rapid AI-enabled prototypes, write production frontend code, evolve the design system, and partner with PMs, engineers, and analysts to deliver delightful, outcome-driven experiences for parents.

Own end-to-end product experiences across web and native mobile: set design vision, run user research, rapidly prototype (AI-enabled), write production frontend code, evolve design systems, mentor designers, and drive measurable product outcomes.

Run strategy and training onboarding sessions, drive customers to first value, manage multiple client cases, own account health and churn prevention, mentor junior teammates, contribute to knowledge base, collaborate with Sales and Enablement, customize onboarding journeys, and identify process improvements to meet KPIs.

As a Software Engineer II, you'll develop generative AI applications, enhance sales operations through AI tools, and collaborate with engineering teams on a remote basis.

Lead design and delivery of production autonomous agents and agentic workflows: architect orchestration, integrate and optimize frontier LLMs, drive model fine-tuning and evaluation, mentor engineers, and translate business goals into safe, reliable, scalable AI-powered product experiences.

Own and improve the AI Social generative media pipeline: build and ship LLM-driven prompts/agent loops, choose and compose media (image, video, voice, music), collaborate with product/design/content, and deliver polished, production-quality social assets.

The Technical Success Consultant delivers services ensuring customer success with AVEVA solutions through workshops, coaching, and strategic guidance while promoting adoption and value realization.

Design, build, and ship production AI systems for Acquia DAM. Architect agentic, stateful multi-agent workflows, own AI observability and RAG architectures, evaluate LLM providers and tooling, mentor engineers, and ensure enterprise-grade security, scalability, and compliance for AI features.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

As a Sr. Applied AI Engineer at Zapier, you will build and enhance AI platform capabilities, focusing on LLM Ops and ML Ops to support scalable AI development across teams.

Lead and grow an engineering team for a large-scale SaaS product, providing hands-on technical leadership, code reviews, and architecture guidance. Collaborate with Product and Design to set roadmaps, contribute to implementation, hire and coach engineers, and support career development and team performance. Foster a feedback culture and adapt processes and technology, especially around AI.

As Principal Product Manager, you'll define product strategy for GitLab's AI models, focusing on custom and self-hosted AI capabilities, collaborating with engineering, and ensuring alignment with company strategy.

As a Staff Machine Learning Engineer, you'll lead AI initiatives using large-scale data, optimize ML models for edge devices, and collaborate with cross-functional teams.

Drive independent, high-impact research on frontier AI topics, publish findings, collaborate widely, and mentor new researchers in the field.

Lead architecture and technical strategy for AI-driven product quality systems using LLMs and agents. Build scalable evaluation frameworks, detect regressions, generate insights, and drive cross-functional adoption while mentoring engineers and defining standards for trustworthy AI.

Lead and own the end-to-end Registry design experience, set vision and KPIs, hire and develop a small design team, use AI-native workflows to prototype and ship cross-platform consumer products, partner with PMs/engineers/analytics, and scale design systems and processes to drive measurable business impact.

Lead large-scale, cross-functional engineering projects to deliver AI-native SaaS features. Own platform architecture for multi-tenant, cloud-native systems, drive engineering standards and developer tooling, mentor engineers, and operationalize LLMs, agent frameworks, and real-time data in production.

Build end-to-end full-stack AI features on a Ruby on Rails backend and React frontend, design and run experiments (A/B tests and AI evaluations), implement AI infrastructure for reliable LLM inference, and iterate quickly to scale production-ready LLM-powered products.

As an AI Transformation Owner at GitLab, you will shape AI strategies, improve workflows, and drive adoption of AI solutions in your organization, working closely with an AI Engineer.

Lead AI-powered sustainability engagements delivering audit-ready GHG inventories, Scope 1-3 calculations, decarbonization planning, and regulatory-ready reporting. Advise executives and auditors, validate AI outputs, analyze ERP and operational datasets, and improve AI models and prompts for consistent, defensible sustainability outcomes.