Top AI Jobs in Ottawa

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.

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 and grow a solution engineering team for AI-powered Dynamics 365 business solutions. Own technical win strategy, coach demos and solution design, partner with sales to convert pipeline, enable value assessments, manage proposals, and align with partners and Customer Success to achieve revenue and deployment outcomes.

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 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.

Design and optimize training and inference systems for LLMs and multimodal models, architect AI integrations into media production (PAM/MAM, studios), evolve GPU infrastructure, lead MLOps/LLMOps, mentor engineers, and ensure secure, low-latency, highly available AI services for 24/7 media workflows.

Design, prototype, and deploy AI-driven applications with a focus on cloud architectures. Fine-tune, evaluate and integrate LLMs, set up testing and monitoring, connect agents to services/APIs, and run exploratory proofs-of-concept. Collaborate with product, architecture and data science teams and use AI-assisted coding tools while maintaining code quality and security.

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

Drive technical pre-sales for Microsoft cloud database and analytics solutions via demos, PoCs, hackathons, and architecture workshops. Design secure, scalable data architectures, resolve technical blockers, collaborate with engineering, and evangelize Microsoft Fabric, Azure Databases, Databricks, Purview and EDW migrations to accelerate customer adoption.

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.

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.

Build, deploy, and maintain AI-powered agents, APIs, and applications for People operations on Snowflake. Integrate Workday/Notion, ensure security and data governance, design multi-model LLM reliability, and own production lifecycle including CI/CD, monitoring, and incident response while working with non-technical stakeholders.

Design and architect large-scale AI systems for media: optimize LLM and multimodal training/inference, evolve GPU infrastructure, integrate AI into production (PAM/MAM/studios), lead MLOps practices, and mentor engineers.

Evaluate AI coding agents end-to-end, judging usefulness, high-level correctness, engineering judgment, and quality of explanations. Provide opinionated feedback, distinguish response quality levels, and help define standards for great AI-developer interactions. Participate in take-home evaluation and interview as part of a rolling, project-based engagement.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Build and deploy production AI/ML features for cybersecurity: design autonomous agent architectures and multi-agent workflows, select and optimize LLMs/SLMs, manage end-to-end ML pipelines, optimize inference and MLOps infrastructure, apply deep learning, time-series and GNN techniques for threat detection, and create automated benchmarking tied to business KPIs.

The Applied AI Backend Sr. Software Developer will design, develop, and maintain SaaS products, mentor junior engineers, and ensure robust backend services using AI tools.

Lead backend development for a cloud-native AI security SaaS: design and deploy scalable microservices and event-driven systems, own features end-to-end, validate AI-generated code for security, implement IaC and CI/CD, mentor engineers, troubleshoot distributed system issues, and collaborate with product, UX, and SRE teams.

Design, develop, test, and maintain macOS endpoint applications and supporting backend services using AI-assisted tools. Own features end-to-end, embed automated testing and CI/CD, collaborate on architecture and quality gates, and prioritize security, reliability, and performance.

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.

The Solutions Engineer supports the sales team by providing technical expertise, conducting demonstrations, designing solutions, and managing complex integrations during the sales cycle.

Support and enhance ADI's global compliance program aligned to enterprise risk and ISO 37301. Monitor regulatory developments, update policies, execute risk‑based monitoring and testing, manage investigations and remediation, support audits, develop training and communications, track metrics, and collaborate with Legal, HR, Finance, IT, and Operations to drive continuous improvement.

Lead and support execution of ADI's global compliance programs: risk‑based monitoring, policy management, testing, investigations, training, ISO 37301 alignment, audits, remediation, and cross‑functional stakeholder coordination.

Lead Andela's marketing strategy across AI services, talent marketplace, and SaaS. Drive brand, demand generation, product marketing, team building, market intelligence, cross-functional GTM alignment, and budget optimization to accelerate growth.