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AI Engineer Sr

Job in Toronto, Ontario, C6A, Canada
Listing for: Dayforce
Full Time position
Listed on 2026-08-06
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Architect, Cloud Engineer - Software, DevOps
Job Description & How to Apply Below

Posted Thursday, July 30, 2026 at 5:00 AM | Expires Thursday, October 1, 2026 at 4:59 AM

Dayforce is a global human capital management (HCM) company headquartered in Toronto, Ontario, and Minneapolis, Minnesota, with operations across North America, Europe, Middle East, Africa (EMEA), and the Asia Pacific Japan (APJ) region.

Our award-winning Cloud HCM platform offers a unified solution database and continuous calculation engine, driving efficiency, productivity and compliance for the global workforce.

Our brand prom ise - Makes Work Life Better ™ - Reflec ts our commitment to employees, customers, partners and communities globally.

About the Opportunity

We are looking for a highly skilled, hands‑on AI Engineer Sr. to design, build, and scale enterprise AI solutions that drive innovation across the organization. This role is ideal for an experienced software engineer who is passionate about applying Generative AI to solve real business problems and enjoys building production‑ready systems.

You will play a key role in developing our AI platform, enabling AI‑powered applications, and building intelligent agents that improve productivity and business outcomes. Working closely with Engineering and Architecture teams, you will help define best practices for AI development while ensuring solutions are secure, observable, scalable, and reusable.

The ideal candidate combines strong software engineering fundamentals with expertise in modern AI frameworks, agentic architectures, and cloud‑native development, along with a passion for building AI‑powered capabilities that create lasting business value and leveraging AI to improve software development and engineering productivity.

What You'll Get to Do
  • Design, develop, and deploy production‑grade AI applications, intelligent agents, and agentic workflows using modern AI frameworks.
  • Build and enhance reusable AI platform components, SDKs, libraries, and services that accelerate AI development across engineering teams.
  • Develop scalable orchestration frameworks for AI agents, tool integration, retrieval pipelines, evaluation harnesses, and model interactions.
  • Partner with Engineering, Architecture, and business services teams to identify, prototype, and deliver AI use cases that improve business processes and developer productivity.
  • Manage and evolve enterprise AI platforms, including OpenAI Enterprise, Anthropic Enterprise, conversational AI platforms, and AI developer productivity tools, while driving platform strategy, governance, security, adoption, usage optimization, and engineering best practices.
  • Build robust evaluation, testing, and monitoring capabilities to ensure AI solutions are reliable, observable, secure, and production‑ready.
  • Implement AI security, privacy, and governance controls, including prompt safety, data protection, guardrails, and responsible AI practices.
  • Leverage AI‑assisted software development throughout the software development lifecycle to improve engineering efficiency and code quality.
  • Contribute to architecture decisions, establish engineering standards, mentor team members, and promote software engineering best practices for AI development.
  • Continuously evaluate emerging AI technologies, frameworks, and industry trends to evolve the organization’s AI capabilities.
Skills and Experience We Value
  • Bachelor's or Master's degree in Computer Science, Software Engineering, Artificial Intelligence, or a related field.
  • Six or more years of professional software engineering experience, with demonstrated experience building scalable, distributed applications.
  • Two or more years of hands‑on experience developing production AI or Generative AI applications.
  • Strong programming skills in Python and experience with modern software engineering practices, including APIs, microservices, CI/CD, and cloud‑native development.
  • Hands‑on experience with AI frameworks such as Lang Graph, Lang Chain, Model Context Protocol (MCP), OpenAI SDK, Anthropic SDK, Semantic Kernel, or similar technologies.
  • Experience designing and developing AI agents, multi‑agent systems, retrieval‑augmented generation (RAG) solutions, tool integrations, and AI orchestration workflows.
  • Experience…
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