Top AI Jobs in Ottawa

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.

Design, build, and ship production AI systems for Acquia DAM. Architect agentic, stateful multi-agent workflows, own AI observability and RAG architectures, evaluate LLM providers and tooling, mentor engineers, and ensure enterprise-grade security, scalability, and compliance for AI features.

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.

As a Senior Software Engineer on the AI Platform, you'll develop scalable AI systems, focusing on backend services, workflows, and integrations, partnering with cross-functional teams.

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across 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.

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.

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.

Lead vision, strategy, and execution for Motives AI camera hardware and firmware. Drive NPIs, prioritize firmware features, write technical PRDs, coordinate cross-functional teams, measure device and AI performance, and enable go-to-market readiness for large-scale connected video devices.

Own end-to-end product experiences across web and native mobile: set design vision, run user research, rapidly prototype (AI-enabled), write production frontend code, evolve design systems, mentor designers, and drive measurable product outcomes.

Lead end-to-end product design across web and native, run user research, build rapid AI-enabled prototypes, write production frontend code, evolve the design system, and partner with PMs, engineers, and analysts to deliver delightful, outcome-driven experiences for parents.

Develop and support AI-driven SaaS solutions, lead architectural decisions, mentor engineers, design scalable microservices, and ensure code quality.

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.

Build agentic applications and tooling with LLM infrastructure, requiring hands-on engineering in a high-pressure environment. Deliver quality under tight deadlines.

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.

The engineer will develop features for an AI workspace platform, deploy AI solutions in public sector environments, and interact with clients.

Lead backend development for AI-enabled SaaS: design scalable microservices, use AI coding assistants, own features end-to-end, enforce code quality/security, mentor engineers, and collaborate with product and SRE teams.

As the Senior Data Scientist for AI & Model Risk, you will lead AI risk assessments, coordinate with stakeholders, evaluate AI system designs, and ensure compliance with risk management principles in financial services.