Systematix is one of North America's most tenured and trusted IT Consulting and Solutions Firms, with offices spread throughout Canada, in the US and UK. For over 40 years we have delivered local, exceptionally cost effective resources and solutions, and never offshore. Our longstanding success if predicated on three core principles: Expertise, Ethics and a Commitment to your Success. Our service catalog is vast, but focuses on 3 key offerings: • IT Consulting • IT Resourcing • IT Solutions We pride ourselves on our geographic capability, regional autonomy, and exceptional client relationships. With over 800 consultants and growing, Systematix is the organization to help you empower your technology, on demand. For more information or openings at Systematix, always go to www.systematix.com
Remote · Canada
Design, implement, automate, and support enterprise identity and access management solutions, including integrations, identity lifecycle processes, and troubleshooting complex access issues. Strengthen identity governance and privileged access capabilities while collaborating with security, infrastructure, HR, and business teams, and providing technical guidance and documentation.
On-site · Montréal
Develop and maintain Oracle applications, reports, forms, and BI Publisher solutions, following established development standards. Collaborate with analysts on analysis and testing, resolve incidents and user-reported defects, support deployments, and contribute to continuous improvement.
Hybrid · Toronto
Develop, configure, integrate, and enhance applications supporting the Listed Derivatives business, while contributing to testing, releases, automation, and solution quality. Provide production support by investigating incidents, resolving application issues, documenting systems and processes, and collaborating with business, operations, IT, vendors, and technology partners.
Remote · Canada
Design, develop, integrate, and continuously improve secure, scalable, accessible .NET applications, APIs, and digital services. Contribute to Agile delivery, DevOps, testing, production stabilization, documentation, and knowledge transfer.
Hybrid · Montréal
Develop, configure, integrate, and maintain applications, while supporting production systems, resolving incidents, and improving application quality, security, performance, and maintainability. Collaborate with technical and business teams on requirements, testing, releases, CI/CD and automation practices, and technical documentation.
Hybrid · Montréal
Implement and maintain observability for AI models, prompts, and agents through instrumentation, logs, metrics, traces, alerts, dashboards, and operational procedures. Monitor usage, costs, quotas, and performance, and optimize AI solutions through routing, caching, and ongoing collaboration with data, AI, architecture, and operations teams.
Hybrid · Montréal
Design and maintain evaluation datasets, test cases, and benchmarks, and conduct automated and human assessments of AI systems before deployment and in production. Analyze system quality, robustness, incidents, and operational metrics; report findings and help improve business rules, prompts, controls, and safeguards.
Hybrid · Montréal
Define target architectures for web and intranet solutions, analyze business and technical requirements, assess market solutions, and contribute to procurement processes. Guide delivery teams and vendors, design application, data, integration, and security architectures, and oversee migration, deployment, production launch, governance, and architectural compliance.
Hybrid · Ottawa
Develop and lead an integrated change strategy for AI transformation, including readiness and impact assessments, stakeholder communications, adoption activities, learning, and leadership support. Define adoption and value measures, report insights, and create reusable playbooks and tools to strengthen organizational change capability and sustain AI adoption.
Hybrid · Montréal
Build, clean, structure, and maintain document corpora and enterprise knowledge resources for AI solutions, including taxonomies, glossaries, ontologies, and semantic repositories. Establish classification and annotation standards, ensure dataset quality and provenance, and collaborate with AI teams to improve semantic search, retrieval-augmented generation, and AI-assisted content generation.
Hybrid · Montréal
Design and conduct experiments to evaluate AI approaches, define suitable metrics and benchmarks, and validate hypotheses to improve model performance and reliability. Analyze model errors, robustness, generalizability, bias, and uncertainty, and collaborate with multidisciplinary teams to operationalize findings and improve AI evaluation and governance practices.
Hybrid · Montréal
Develop and apply artificial intelligence models to geospatial data, including geomatics, remote sensing, and imagery, to support better decision-making. Identify and prioritize high-value use cases and collaborate with multidisciplinary teams to deliver solutions combining AI, advanced analytics, and geospatial technologies.
Hybrid · Montréal
Facilitate Agile delivery for multidisciplinary data and AI teams, including ceremonies, sprint planning, backlog management, estimation, and delivery tracking in Jira. Identify and help resolve blockers, monitor risks and dependencies, collaborate with technical specialists and stakeholders, and promote continuous improvement.
Hybrid · Montréal
Design and develop AI-based computer vision solutions, processing and analyzing images, videos, and other visual data to automate visual analysis and improve operational processes. Identify valuable use cases, collaborate with multidisciplinary teams, and train, evaluate, and continuously improve computer vision models for innovative AI and advanced analytics projects.
Hybrid · Montréal
Translate business needs into measurable analytical problems, explore and prepare data, and design experiments to assess potential solutions. Develop, evaluate, document, and improve statistical and machine-learning models, while collaborating with data, AI, and engineering teams to deploy and monitor them in production.
Hybrid · Montréal
Design, build, and evolve platform capabilities and reusable services for data, analytics, and AI teams, including infrastructure automation and model hosting and deployment. Ensure the platform is secure, resilient, performant, available, cost-optimized, and compliant while collaborating with data, engineering, and AI teams.
On-site · Montréal
Secure AI solutions, models, agents, data, and their interactions with enterprise systems by implementing controls for sensitive data, access, content filtering, and AI-specific threats. Conduct security reviews, maintain audit logs, assess risks, and recommend proportionate mitigation measures aligned with organizational and cloud security requirements.
On-site · Montréal
Design a cross-functional trust architecture for AI solutions, defining safeguards, resilience properties, human oversight, lifecycle controls, and mechanisms for monitoring, shutdown, recovery, and controlled degradation. Identify and manage AI risks and failure scenarios, establish traceability and auditability requirements, and prepare defensible evidence for architecture reviews, risk assessments, and audits.
On-site · Montréal
Design AI system architectures and reusable patterns across traditional, generative, and agentic AI, including retrieval-augmented pipelines, agent orchestration, model routing, and MCP interoperability. Integrate models, data, APIs, and applications across Azure and Databricks environments, and guide teams through design reviews and production deployment.
Hybrid · Montréal
Configure and evolve data governance and cataloging platforms, including governance models, policies, metadata synchronization, lineage, classification, and quality mechanisms. Manage roles and permissions, create governance dashboards, and support teams and data owners through documentation, training, and adoption of data and AI governance practices.
