Top AI Jobs in Ottawa

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.

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.

Execute technical and content SEO, local SEO, and AI discoverability for ecommerce and content-heavy sites. Perform audits, implement structured data/schema, on-page optimization, keyword research, Google Business Profile management, and use GA4/Search Console/Looker Studio and SEO tools to tie search performance to business KPIs while partnering with cross-functional teams.

Develop AI solutions and enhance observability data using AI-powered features. Collaborate cross-functionally, iterate rapidly, and take ownership of AI projects while ensuring scalability and impact.

The AI Engineer will develop GenAI solutions, manage production rollouts, advise customers, and collaborate across teams to enhance AI applications.

Design and develop machine learning models for multimodal data integration, collaborating with scientists and engineers to create scalable solutions.

As a Software Engineer, AI, you'll train large-language models by comparing, ranking, and refining AI-coded snippets, while providing feedback for reinforcement learning.

The Software Engineer will analyze, rank, and improve AI-generated code, providing feedback for reinforcement learning in a remote role.

Train large-language models (LLMs) by evaluating, ranking, repairing, and refactoring code. Provide detailed feedback and maintain the RLHF pipeline.

The role involves training large-language models to improve code generation, reviewing and editing AI-generated code, and providing feedback for reinforcement learning refinement.

Lead and manage the MCP and Agentic AI engineering teams, overseeing project execution, technical vision, and team development while integrating AI technologies into products.

Lead the development and execution of internal AI solutions, prioritize features, define product requirements, and communicate across teams to measure impact.

The AI/ML Engineer will design and develop AI-powered applications, automate workflows, and integrate AI into BPM's daily operations, ensuring they deliver business value.

The Sales Development Representative will drive outbound prospecting efforts, achieve sales goals, collaborate with Account Executives, and maintain CRM records while engaging technical buyers.

The Regional Sales Manager leads revenue strategy for AI Native across Western US, managing a team of 8 Account Executives, and driving regional performance, pipeline generation, and strategic growth.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

The Research Engineer will develop the DeOS framework, optimizing AI workloads, managing GPU resources, ensuring scalability, and contributing to open-source projects.

Design and implement advanced Generative AI models, optimize performance for LLMs, and collaborate with cross-functional teams to innovate AI solutions within the automotive sector.

Design and implement advanced generative AI models, optimize deployment in production, collaborate with teams, and stay updated on AI advancements.

Lead the development of AI-driven security workflows, integrate machine learning models, establish data pipelines, and mentor engineers.