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Updated 2026-06-22 20:00 UTC·© 2025–2026 RoleSuite
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Senior AI Engineer

Jobgether · Canada

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior AI Engineer based in Canada.

This is a high-impact engineering role focused on building production-grade AI agent systems that power large-scale marketing and revenue operations. You will design and deploy multi-agent architectures, LLM-driven workflows, and backend infrastructure that automate complex business processes across global teams. The work sits at the intersection of AI engineering, distributed systems, and real-world business optimization. You will own the full lifecycle of AI systems—from architecture and development to deployment, monitoring, and continuous improvement. This role offers high autonomy, allowing you to define technical direction and choose the best tools and frameworks for scalable solutions. You will collaborate closely with cross-functional stakeholders to translate operational bottlenecks into intelligent automation. The environment is fast-paced, highly technical, and deeply rooted in open-source and cloud-native engineering culture.

Accountabilities:

  • Design, build, and maintain production-grade multi-agent AI systems that automate workflows across marketing, revenue operations, and sales teams.
  • Develop and scale LLM-powered infrastructure including orchestration frameworks, agent pipelines, and reusable AI components used across internal platforms.
  • Build backend services, APIs, MCP servers, and microservices that connect AI systems to enterprise tools such as CRMs, data warehouses, and communication platforms.
  • Implement retrieval-augmented generation (RAG) pipelines, data integrations, and real-time context systems to enhance AI decision-making.
  • Establish observability frameworks for AI systems including monitoring, evaluation, logging, performance tracking, and cost optimization.
  • Define governance standards for AI workflows, including security, compliance, access control, and human-in-the-loop escalation paths.
  • Partner with cross-functional teams to identify high-impact automation opportunities and translate them into scalable technical solutions.
  • Build self-service automation platforms with clear documentation, APIs, and tooling to enable non-technical teams.
  • Continuously improve system reliability, scalability, and efficiency through experimentation and iterative engineering.
  • Requirements:

    • 8+ years of software engineering experience with strong expertise in backend systems, data engineering, or distributed systems.
    • 2+ years of hands-on experience building production AI/LLM-powered systems beyond prototypes.
    • Strong proficiency in Python and JavaScript/Node.js with solid engineering practices (testing, CI/CD, Git workflows).
    • Deep experience with LLM frameworks and patterns including prompt engineering, tool use/function calling, RAG, and evaluation techniques.
    • Proven experience designing and operating multi-agent systems with orchestration patterns, state management, and production monitoring.
    • Strong understanding of cloud infrastructure, preferably Google Cloud Platform, including serverless and containerized architectures.
    • Experience identifying high-leverage business problems and translating them into scalable technical solutions.
    • Solid grasp of LLM production challenges such as latency, cost control, fallback mechanisms, and failure handling.
    • Strong communication skills with the ability to bridge technical complexity and business impact.
    • Preferred: experience with vector databases, workflow orchestration tools, observability frameworks, and marketing/sales tech stacks.
    • Preferred: familiarity with MCP standards, open-source ecosystems, or automation in B2B SaaS environments.
    • Benefits:

      • Competitive compensation aligned with experience and market standards, including base salary and equity (RSUs)
      • Fully remote work within Canada with global collaboration opportunities
      • 30 days of annual leave including dedicated company shutdown periods
      • Comprehensive health, dental, and wellness coverage
      • Home office setup support and productivity allowances (where applicable)
      • Learning budget and continuous professional development opportunities
      • Access to advanced AI tools and developer productivity platforms
      • Strong open-source culture with high autonomy and engineering ownership.

AI Engineering pay context

Based on 566 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $200K/year, with most offers between $162K and $237K (10th–90th percentile: $131K–$272K).

See the full AI Engineering salary breakdown →
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