Top AI Jobs in Ottawa

Lead cross-functional teams to architect, build, and deliver cloud-native, enterprise-grade web applications. Drive AI-native development practices, spec-driven workflows, and use of AI coding agents. Oversee frontend and backend architecture, APIs, integrations, CI/CD, containerization, and observability while mentoring teams and partnering with stakeholders to meet client objectives.

Design, prototype, and deliver production-grade agentic AI applications and cloud-native systems. Build multi-provider agent architectures, orchestration, retrieval/RAG, observability, and scalable microservice or serverless integrations while advising clients and guiding adoption of AI-native development practices.

The Enterprise Architect will design data-centric systems, lead technical policy implementation, and collaborate with partners while addressing cybersecurity and system architecture requirements.

Lead the product strategy for Scribd's internal developer and agentic platforms: unify AI workstreams, own internal app/plugin/agent runtimes, translate functional needs into platform requirements, drive cross-functional adoption and metrics, and run internal rollouts and evaluation to prove impact.

Founding GTM rep responsible for building and qualifying pipeline across enterprises and AI startups, managing inbound requests and outreach automations, re-engaging sign-ups, coordinating discovery calls with founders/CRO, tracking CRM and pipeline metrics, attending events, and proposing GTM experiments and partnerships.

The Account Executive will manage the full sales cycle for enterprise and scale-up accounts, building relationships with technical buyers and collaborating closely with senior leadership to drive revenue and shape sales strategies.

Intern will help design and implement the openJiuwen AI Agent Platform and enterprise data foundations: knowledge graphs, vector DBs, workflows, agent frameworks, tool-calling, and multi-agent systems. Contribute to open-source projects (JiuwenSwarm), build real-world AI agents, explore LLM, RAG, memory, planning, and evaluation technologies, and support documentation and community collaboration.

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.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide clear, opinionated feedback, distinguish response quality levels, and help define best practices for AI-assisted developer workflows.

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.

Lead technical presales for Azure cloud and AI infrastructure: design secure, scalable architectures, drive migrations and modernization (6R, containers, AKS, App Service), run workshops, demos and PoCs, resolve technical blockers, collaborate with account teams and partners, and translate technical solutions into business outcomes for public sector customers.

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.

Join the AI, automation, and business innovation team to identify automation opportunities, map processes, prototype and deploy solutions using Power Automate, Python, and GPT/Claude, analyze and clean large datasets, create documentation and training, build departmental super users, and measure/report outcomes to senior management.

The role involves leading as a thought leader in technology operations and AI implementation, mentoring executives, advising on technology strategies, and producing actionable insights for clients.

Build and maintain backend features for Agent Observability across the GitLab monolith and AI gateway. Design and implement GraphQL/REST APIs, improve automated tests (RSpec), collaborate cross-functionally, troubleshoot production issues on Tier 2 on-call, and help shape responsible AI integration and platform architecture.

As an Applied AI Junior Web Developer, you'll build modern websites, utilize AI tools, and develop testing skills while creating a user-friendly digital presence for Trend Micro's cybersecurity solutions.

As a Junior Web Developer, you'll create modern websites using AI tools. Responsibilities include coding, debugging, testing, and continuous learning to enhance web experiences for TrendAI.

Trend Micro is seeking an Applied AI Sr. Front-End Developer to design micro-frontend applications, enhance productivity using AI, and lead testing strategies while mentoring team members in a collaborative environment.

Develop frameworks for serverless computing optimized for AI workloads, analyze AI system performance, and evaluate emerging technologies.

The role involves researching AI/ML concepts for OS, implementing advanced technologies, and optimizing performance and resource management in embedded systems.

The role involves developing AI-based IDE technologies to improve software development efficiency, collaborating on language and compiler capabilities, and prototyping innovations for developers.

Create hands-on, on-camera educational content teaching AI tools and workflows. Test and evaluate new AI tools, script and record lessons, host live sessions and office hours, provide personalised feedback, and collaborate to build courses, guides, and workshops for a large AI community.

The Engineering Manager will drive operational excellence, guide technical execution, coach engineers, foster collaboration, and integrate AI-assisted development practices.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

Design and optimize high-performance Edge AI software for NXP embedded SoCs, enabling deployment of ML and generative AI models. Implement and integrate AI runtimes, inference engines, and model pipelines, drive system-level performance tuning (latency, memory, power), validate and productionize solutions, and collaborate across silicon, system, and AI teams to deliver end-to-end Edge AI platforms.