Top AI Jobs in Calgary

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

As a Social Media Intern at Inception, you will manage social content across platforms, engage with AI discussions, participate in product launches, and create engaging video content. Aimed at students with a passion for AI and strong writing skills, the role offers direct access to the founding team and the potential for full-time conversion.

As a Chatdesk Expert, provide customer support for brands through social media and email. Set your own schedule and work remotely.

Lead and scale Mimica's product organisation, define global product strategy and roadmap for AI-driven task/process mining and automation, mentor product and design teams, improve product operations and discovery, align cross-functional stakeholders, handle escalations, and hire and forecast team needs.

The AI Engineer will design, develop, and deploy AI-powered systems, improve operations with intelligent workflows, and collaborate on high-leverage AI opportunities.

Lead architecture and evolution of Juniper Square’s distributed services, cloud infrastructure, and developer platform. Design scalable, multi-tenant, event-driven systems; build paved-road developer tooling, CI/CD, and observability. Hands-on coding, prototyping, and performance troubleshooting. Enable production AI/LLM workloads, ensure security/compliance, support enterprise upmarket needs, and mentor engineering teams to raise operational excellence and reliability.

The AI Infrastructure Engineer designs, develops, and optimizes core capabilities for the AI inference platform, focusing on reliability, scalability, and operability of infrastructure and services.

Lead identification, prioritization, and implementation of AI-driven use cases and automation across global programs. Drive POCs, design future-state workflows, gather requirements, build governance, create AI-enabled dashboards and playbooks, partner with IT/vendors, and train teams to increase adoption and operational efficiency.

Design, prototype, and ship production AI/ML features that analyze observability data to detect, triage, and resolve incidents. Rapidly iterate on LLM- and agent-powered workflows, collaborate cross-functionally, integrate AI with internal tools and alerting systems, and ensure solutions are scalable, maintainable, and aligned with user workflows.

Lead and grow a Vincent AI software engineering team: collaborate with product and design, design technical solutions, perform code reviews and hands-on development, hire and coach engineers, drive roadmaps, and improve processes with an AI focus.

Lead cross-functional technical and writing teams to deliver NEMO LLM products. Liaise with customers, product, research, and DataFactory teams; track annotator metrics; write prompts/responses; manage labeling initiatives; develop guidelines; train stakeholders; and handle potentially toxic or sensitive content.

Design, build, and productionize LLM-powered applications and agentic AI systems. Develop data and inference pipelines, deploy and monitor models, define evaluation frameworks, optimize performance/cost, and enforce governance, safety, and observability to deliver scalable AI-driven customer experience solutions.

Lead AI enablement across workflows and products: evaluate and pilot third-party AI tools, partner with IT and Compliance, co-develop low-code/no-code agents, design testing and rollout plans, create documentation and upskilling collateral, run demos and training, and present actionable recommendations to stakeholders to drive business impact.

Join as a founding GTM team member to build and qualify pipeline, manage inbound chats/emails, run outreach automations, re-engage sign-ups, track CRM and metrics, and attend events to generate high-value relationships with developers, startups, and enterprises in the open AI ecosystem.

Full-cycle AE responsible for sourcing, qualifying, negotiating, and closing mid-market and enterprise AI cloud deals. Build technical relationships with CTOs and ML engineers, run demos, craft proposals, manage CRM (HubSpot), and help define GTM and expansion motions while mentoring BDRs.

The Senior Developer, Enterprise AI will lead the design and implementation of AI-enabled workflows, collaborating with cross-functional teams to develop secure and scalable solutions while mentoring junior developers.

Develop and deploy generative AI and LLM solutions end-to-end for e-commerce: research models, build ETL/data pipelines, run distributed training and experiments, collaborate with product and engineering to deliver production systems that improve recommendations, search, personalization, and customer interactions.

Research-focused internship for advanced PhD candidates to develop and evaluate neurosymbolic, knowledge representation, multimodal, and trustworthy AI methods. Duties include defining research questions, building prototypes and benchmarks, running rigorous experiments, collaborating with engineers and domain experts, and moving research toward production and publications.

Support Data Science and Regulatory Affairs to define and execute regulatory strategies for AI/ML-enabled medical devices. Translate ML concepts into regulatory documentation, create DHF and submission materials (510(k), EU MDR, Health Canada), maintain dataset and model documentation, and manage version control and change management.

Founding research hire to develop clinical reasoning and computer-use models using proprietary hospital and clinic data. Own end-to-end training and evaluation pipelines, design benchmarks exposing LLM weaknesses on clinical reasoning, run experiments, and publish technical reports and papers. Collaborate closely with founders and deploy research into products that improve physician 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.

Design, build, and ship end-to-end AI and data solutions using proprietary data infrastructure. Scope projects with business stakeholders, implement models, pipelines, and APIs (Python/SQL), deploy on Snowflake or BigQuery, and iterate post-launch. Enable non-technical teams, collaborate with Data Engineering and AI teams, and operationalize LLMs, embeddings, and predictive models into working internal products.