Top AI Jobs in Ottawa

Develop production radio software, automated tests, ML/AI troubleshooting tools, and software-hardware integration tests. Troubleshoot testing issues, verify delivered functionality in laboratory environments, review software designs and test plans, and report test results. The role is a 12–16 month co-op requiring full-time enrollment in a relevant engineering or computer science program and availability for 40 hours per week.

Lead complex security incident investigations from assessment through recovery, coordinating containment, remediation, evidence preservation, and stakeholder communication. Analyze threats across endpoint, identity, cloud, SaaS, network, and application environments. Build code, queries, automation, and AI-assisted workflows to improve evidence collection, detection, case management, and response. Lead post-incident reviews, drive lasting improvements, mentor responders, and participate in the incident response on-call rotation.

Supports the governance, risk, and compliance program with a focus on third-party risk management. Conducts vendor assessments, maintains security policies and standards, performs risk analysis, supports SOC 2 audits, gathers evidence, tracks findings, and conducts internal audits. The role also uses AI and machine learning tools to improve GRC processes and promotes security awareness across the organization.

Build infrastructure and tooling for AI evaluation, including distributed execution, task-set validation, graders, human-review calibration, statistical reporting, online feedback loops, and offline-to-online analysis. Partner with product, engineering, data, and ML teams to create reliable evaluation workflows that support faster, statistically sound AI product decisions.

Leads Dropbox’s global Revenue and Marketing Operations strategy across SMB, Mid-Market, and Enterprise segments. Owns revenue planning, forecasting, segmentation, territories, quotas, incentives, GTM systems, analytics, productivity, and operating cadence. Partners with executive leadership across Sales, Marketing, Finance, Product, Customer Success, and Support to drive scalable growth, AI adoption, systems transformation, and revenue predictability. Builds and develops a high-performing global Revenue Operations organization.

Develop and prosecute patent applications involving 5G/6G, cloud, AI, software, and advanced communications. Evaluate inventions, prepare claim charts, manage patent cases and portfolios, and collaborate with inventors, researchers, and university partners globally. The role also supports licensing and litigation activities and contributes to Ericsson’s large-scale intellectual property strategy using AI-enabled tools.

Leads strategic pricing and monetization across sales-driven channels, managing pricing partners and advising on complex commercial deals. Develops pricing frameworks, approval processes, deal governance, and scalable tools using automation, AI, and data. Partners with Sales, Product, Engineering, Legal, Risk, and Revenue Operations to improve deal economics, profitability, pricing performance, packaging, and portfolio-level monetization strategy.

Create technical content, videos, demos, presentations, and product walkthroughs showcasing GitLab’s DevSecOps and AI agent capabilities. Engage developers, customers, sales teams, and online communities through webinars, events, forums, Discord, and social platforms. Answer technical questions, deliver analyst briefings, research the developer tools landscape, test new features, and provide product feedback. The role is remote, supports U.S. and Canadian time zones, and requires up to 20% travel.

Owns analytics and optimization strategy for advertising revenue across Zynga’s mobile game portfolio. Responsibilities include monitoring performance, diagnosing trends, designing A/B tests, identifying monetization opportunities, partnering with product, analytics, and data science teams, supporting AI and ML models, leading cross-functional initiatives, and mentoring analysts.

Leads Square’s US Business Development Representative organization through managers and frontline teams. Owns pipeline generation strategy, operating cadence, performance management, forecasting, capacity planning, outbound execution, and sales technology improvements. Coaches managers, develops BDR talent, hires and retains staff, and partners with Sales, Marketing, Revenue Operations, Enablement, Analytics, and Strategy to improve funnel conversion and revenue contribution. Uses data, automation, AI, and prospecting tools to improve productivity and scale successful programs.

Own IT internal audit projects and portions of the SOX program, including ITGC and ITAC testing, risk assessment, controls evaluation, remediation, and audit reporting. Partner with audit, finance, engineering, process owners, external auditors, and co-sourcing partners. Help establish an AI audit methodology and implement AI-enabled audit efficiencies while maintaining quality, independence, and reliability.

Develop and own scalable AI-enabled software and data engineering solutions for RAN reliability and customer deployments. Build ingestion and processing pipelines, AI-ready datasets, and secure integrations into Git, Gerrit, CI/CD, testing, and development workflows. Transform prototypes into maintainable products while ensuring data quality, traceability, access control, monitoring, and vulnerability management. Collaborate with engineers, data scientists, architects, and product stakeholders, provide mentorship, and promote responsible AI-assisted development.

Own regional Sales Operations infrastructure for NAMER, including territory and quota planning, account segmentation, forecasting governance, pipeline inspection, CRM hygiene, executive reporting, and operational cadence. Partner with Sales, Finance, Compensation, Systems, Analytics, and Enablement to improve coverage, forecast accuracy, workflow automation, and sales execution. Support organization design, onboarding, incentive programs, and channel deal registration while applying AI-enabled tools and sound business judgment.

Develops AI-powered solutions for system verification, testing, and engineering workflows. Responsibilities include building Generative AI, LLM, RAG, and agentic AI applications; integrating AI tools with engineering systems; analyzing quality and testing data; supporting proof-of-concepts; and creating dashboards and visualizations. The role collaborates with verification engineers, test managers, and software developers to improve automation, productivity, and product quality.

Leads Accenture’s Quebec AI agenda, including market strategy, sales, solution architecture, production delivery, responsible AI, data governance, privacy, and sovereign deployments. Owns portfolio quality, risk, margin, and operationalization of generative and agentic AI systems. Builds reference architectures, delivery standards, reusable accelerators, and a bilingual technical team while advising executive stakeholders and representing Accenture across Quebec’s AI ecosystem.

Teach an in-person graduate course on advanced medical instrumentation, covering medical diagnosis systems, biosensors, diagnostic imaging, laboratory tests, vital-signal acquisition and processing, artificial intelligence, and automated diagnostic products. The instructor will integrate theoretical and practical engineering concepts and guide students in applying them to medical diagnostic technologies.

Teach a three-credit, in-person course on advanced artificial intelligence, including agentic and multi-agent systems, autonomous task execution, resource coordination, system design, orchestration, governance, and deployment across scientific, industrial, and engineering environments.

Teach an in-person, three-credit course on agentic AI systems innovation and design during the Winter 2027 semester. The course covers autonomous and multi-agent systems, task execution, resource coordination, goal achievement, system orchestration, governance, and deployment across engineering and industrial environments. Candidates must hold a PhD in Mechanical Engineering, have extensive relevant research experience, and be licensed or eligible for professional engineering licensure in Canada.

Advances People & Culture technology through Workday configuration, automation, AI, and process improvement. Partners with HR stakeholders, Workday analysts, project managers, and IT to define requirements, develop scalable solutions, improve employee experience, and maintain privacy, legal, security, and ethical standards. Manages multiple global initiatives across more than 37 countries.

Analyzes the exposure management competitive landscape, synthesizes technical and market intelligence, conducts win/loss analysis, supports competitive deals, develops field enablement materials, and recommends product and go-to-market strategies. Partners with Product, Sales, Marketing, Strategy, Investor Relations, and senior leadership to translate complex cybersecurity concepts into actionable guidance and executive insights.

Lead global industry analyst relations and support North American public relations initiatives. Develop engagement strategies, manage analyst briefings and evaluations, strengthen media relationships, create executive and thought leadership content, secure interviews and speaking opportunities, oversee PR agencies, and use market, competitive, analyst, and media insights to improve QNX positioning and communications effectiveness.

Lead product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

Build infrastructure and tooling for AI evaluations, including distributed scoring engines, task-set validation, grader systems, human-review calibration, statistical leaderboards, online feedback capture, and offline-to-online evaluation loops. Partner with product, engineering, data, and ML teams to deliver reliable, observable evaluation workflows that support faster and more trustworthy AI product development.

Owns enterprise AI customer deployments from discovery and product scoping through delivery, adoption, and measurable value. Translates customer workflows into product requirements, deployment roadmaps, and technical solutions while partnering with engineering, sales, finance, legal, security, and customer success. Evaluates AI-specific considerations, business cases, risks, and product opportunities, then converts recurring customer needs into scalable capabilities and operating playbooks.

Leads complex data science and analytics initiatives, develops and validates predictive models, evaluates diverse data sources, and translates findings into actionable business insights. Determines technical approaches, supports risk mitigation and decision-making, and provides technical leadership and mentorship to analytics professionals. Collaborates with stakeholders while promoting quality, consistency, and data-driven solutions.