Top AI Jobs in Ottawa

The Senior AI Developer will create and integrate AI-powered features into a practice management platform, focusing on LLMs and agentic AI. Responsibilities include feature design, architecture implementation, collaboration with teams, and evaluation of emerging AI technologies.

Lead the AI tooling strategy for engineering, enhance developer tools, collaborate with teams, and mentor engineers to improve workflows and productivity.

The AI Transformation Lead will drive AI delivery capabilities, transforming internal operations and client programs, while embedding AI practices and managing teams to ensure successful implementation and measurable outcomes.

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.

As an AI/ML Engineer Intern, contribute to designing and deploying machine learning systems, automate workflows, build data pipelines, and collaborate with experienced teams to solve high-impact problems.

As an AI Product Intern, you'll design, develop, and deploy AI-powered software, working closely with teams to solve real-world problems and improve applications based on user feedback.

As a Product Manager for Platform Intelligence, you will lead the AI/ML strategy for the Accelerant Risk Exchange, collaborating across teams to enhance decision-making tools for specialty insurance risk management.

Lead the engineering team to develop AI and data products on the Azure platform, manage product features, and improve application performance.

Lead AI diligence engagements for private equity, evaluating AI strategies and identifying opportunities in target companies. Manage client relationships and collaborate with product and engineering teams to implement AI solutions.

The Senior AI/ML Engineer will architect, build, and deploy AI systems, working with clients to understand their needs and applying MLOps practices to enhance AI services.

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.

Lead global positioning and go-to-market strategies for connectivity products in AI data centers, emphasizing high-speed low-latency technologies.

As a Full Stack Engineer, you'll develop production-ready AI and ML features, build APIs, design scalable systems, and implement frontend solutions using Angular.

Lead development of AI-driven features, manage integrations and teams, oversee product strategy, and cultivate relationships to drive business growth.

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.

Drive AI adoption across the organization by building and deploying AI solutions, integrating systems, and ensuring effective training and governance.

As an AI Strategist, guide organizations in adopting AI by translating business challenges into clear use cases, aligning with enterprise architecture, and influencing high-impact decisions across teams.

The AI Principal Engineer will drive the AI product vision, collaborate closely with the CEO, design key features, and lead a team of AI engineers in a fast-paced startup environment.

The role involves ensuring the reliability of Veeva AI Agents through evaluation strategies, LLM output integrity assessments, and automation of evaluation pipelines while debugging and reporting performance metrics.

Partner with executive sponsors and end users to identify high-impact AI use cases on Glean, run discovery workshops, scope pilots, build AI agents, drive adoption and expansion, and translate business needs into measurable outcomes.

This internship opportunity is for students in computer engineering or AI to work on distributed systems at Bedrock Security.

Lead end-to-end full-stack feature development using AI agents across frontend and backend: own requirements, architecture, implementation, testing, rollout, and monitoring while improving AI-native engineering workflows and reliability.

Architect, develop, and deploy agentic and multi-modal AI systems for biopharma and healthcare. Build scalable production software, data pipelines, and model serving in cloud environments (AWS). Lead full development lifecycle, implement CI/CD/DevOps best practices, mentor junior engineers, and collaborate with researchers and product teams to operationalize AI solutions.

Lead and scale forward-deployed engineering pods to convert complex customer workflows into production AI agent deployments. Build operating cadence, quality bars, deployment playbooks, partner with product, and hire/coach leaders while staying technically hands-on to ensure reliable, observable, and safe agent systems.