Top AI Jobs in Ottawa

Develop AI-driven applications and agentic workflows using TypeScript, Nest.js, LangChain, LangGraph, and LLM integrations. Build Java-based REST APIs and backend systems using distributed and big-data technologies. Collaborate with product, design, frontend, and backend teams to deliver features, test and review code, refactor systems, and support continuous improvement.

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 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.

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.

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.

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.

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

Drive Azure adoption and AI/data platform consumption across Western Canada by engaging CXO-level stakeholders, building business cases, leading virtual sales and partner teams, identifying and closing opportunities, and removing deployment roadblocks to achieve quarterly Azure consumption targets.

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.

Manage a cross-functional engineering team building GitLab Duo Chat's AI-powered features. Define requirements with product and UX, contribute to architecture for scalable agentic AI, drive delivery and roadmap execution, improve testing, observability, performance, and coach engineers to foster an inclusive, high-performing team.

Lead design and implementation of modular, high-performance web experiences using Astro/React/TypeScript. Define AI-enabled developer workflows, mentor junior developers, customize Sanity CMS, manage AWS deployments with IaC (CDK), and enforce test-driven quality using unit and E2E frameworks (Cypress/Playwright). Champion ethical AI tooling adoption and continuous front-end architecture improvements.

Design, build, and deploy production-grade AI/ML features and autonomous agent systems for cybersecurity. Own end-to-end ML pipelines, model selection and optimization, inference engineering (quantization/pruning/TensorRT), multi-agent orchestration, GNN/time-series analytics, benchmarking, and MLOps for the Trend Vision One platform.

Lead and grow an AI engineering organization responsible for delivering enterprise-grade AI applications across business functions. Establish architecture, engineering standards, deployment practices, and technical strategy for scalable AI systems. Mentor engineers, oversee cloud infrastructure, data pipelines, model serving, monitoring, and continuous improvement. Partner with product, data science, and business stakeholders while ensuring security, compliance, governance, reliability, and performance across globally distributed teams.

Lead end-to-end design for AI-powered developer tools at GitLab. Create flows, wireframes, prototypes, and high-fidelity interfaces for AI agents, chat, and code-assist features. Define success metrics, iterate with PMs and engineers, establish AI-specific design patterns in the design system, mentor other designers, and contribute to product strategy and research-informed decisions.

Lead multi-year vision, strategy, and roadmap for Webflow's agent surfaces and AI platform. Align cross-functional teams, set quality standards and guardrails for non-deterministic agent experiences, serve both developers and creators, prototype and ship product improvements (including contributing code), and mentor PMs while measuring and iterating on outcomes.

Lead product strategy and roadmap for Webflow's agentic AI surfaces (AI Assistant, MCP, Agent Instructions, and underlying AI platform). Define quality metrics, guardrails, and evaluations for non-deterministic agent experiences. Balance developer-focused APIs/platforms with approachable creator UX, work closely with engineering/design/data, prototype and ship features (including contributing code), and adapt strategy as AI models and protocols evolve.

Lead architectural vision and technical strategy for enterprise private cloud platforms. Design end-to-end solutions across Kubernetes, OpenStack, analytics, and automation, enable AI/ML workloads with accelerator support, define reference architectures, guide security-by-design, run proofs-of-concept, and mentor engineering teams.

Teaching the course on Generative AI and Large Language Models, focusing on model development, deployment, and practical applications in diverse domains.

Lead strategy and execution for agentic AI product experiences across the DFIR portfolio. Define roadmaps, ship reliable and governed agentic features, drive adoption and growth, instrument metrics and experiments, run continuous discovery, and collaborate cross-functionally to ensure trustworthy, scalable AI-native products.

Intern will build enterprise data foundations and AI agents connecting LLMs to authoritative business knowledge. Responsibilities include developing retrieval/RAG pipelines, agent workflows, persistent memory/state management, governance controls, auditability, and integrations with vector DBs, knowledge graphs, enterprise tools, and multiple LLM providers.

Lead a distributed AI/ML engineering team to deliver production-grade AI systems for manufacturing. Define technical vision, prioritize high-impact use cases (yield, quality, maintenance, inspection), design scalable architectures, partner with site and enterprise teams, ensure responsible AI governance, and drive adoption and measurable operational improvements across plants.

Evaluate AI-generated coding interactions end-to-end, judging usefulness, high-level correctness, engineering judgment, explanations, and reasoning. Provide clear, opinionated feedback, distinguish quality levels, and help define standards for excellent AI-assisted developer interactions.

Contract senior engineer evaluates AI coding agent interactions (Codex, Claude Code) for engineering judgment, reasoning quality, usefulness, and alignment with strong developer practices; provides opinionated feedback and helps define high-quality interaction standards. ~10-20 hrs/week, $100-$200/hr, short-term through early May.