Dayforce
[WINTER 2027] AI App & Tool Development Intern 8 Months
Toronto, Ontario, Canada
On-site · $28.2–$31.79 (as posted)
First seen by offpeak October 24, 2026
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Benefits for Students:
- Experience working for one of the fastest growing Human Capital Management technology companies in the world
- Access to Dayforce development programs and resources
- Ability to work with, as well as create relationships with, Dayforce team members across the globe
- Autonomy to bring forth new ideas and optimize existing structures within the organization
- Meaningful responsibilities, enabling you to obtain ‘real-world’ experience
- Dynamic hands-on exposure to multiple business-units and stakeholders across Dayforce
About the opportunity:
We’re looking for an AI App & Tool Development Intern to help design and build AI-powered tools, automation, and product improvements that make our teams more effective.
You’ll work directly with the Application Advisory (AA) team, engineers, consultants, and other stakeholders to identify high-value problems and turn them into working solutions. Projects may range from enhancing existing internal tools, developing new AI-powered applications and automating complex workflows.
One of our key initiatives is using AI and/or automation to significantly reduce the manual effort involved in Dayforce release smoke-testing, with a goal of reducing testing effort by more than 50%. But that is only one example of the problems you may tackle.
The common thread is simple: find high-friction work, understand the problem, and build technology that makes it better.
You’ll write code that ships. You’ll prototype quickly, work with the people who actually use the tools, measure whether your solution creates meaningful value, and iterate based on what you learn.
What you’ll get to do:
- Build and enhance internal tools and applications used by the Application Advisory team
- Contribute to the evolution of existing tools, including enabling Advisory to use developer forward Dayforce tools like Studio and APIs
- Identify repetitive, manual, or high-friction workflows that can be improved through software, AI, or automation
- Design and prototype new tools based on real business and user requirements
- Build AI-powered workflows using LLM orchestration, RAG, agentic patterns, and Azure AI
- Work directly with Advisory team members and implementation consultants to understand workflows and translate business problems into technical solutions
- Develop backend services and integrations using Python, SQL, APIs, and Azure technologies
- Build and improve user experiences using JavaScript and React
- Integrate Dayforce and internal systems where appropriate to create more connected workflows
- Measure the impact of what you build through metrics such as hours saved, adoption, workflow efficiency, test coverage, and quality improvements
- Take successful prototypes beyond the proof-of-concept stage and help turn them into reliable tools people can use
- Document solutions and communicate findings to both technical and non-technical audiences
Types of Projects You May Work On
Your projects will be driven by real AA business needs and may include:
- Clock Order enhancements — improving the standard operating procedure, with focus on visibility and automation
- AI-powered internal tools — building assistants and applications that help Advisory teams complete work faster
- Implementation test automation — reducing manual configuration validation, scenario testing, and parallel verification
- Workflow automation — replacing repetitive processes with intelligent, automated workflows
- Knowledge and RAG solutions — making internal knowledge easier to find and use in context
- Agentic workflows — developing AI agents capable of completing multi-step tasks across systems
- Data and reporting tools — turning operational data into actionable insights
- Rapid prototypes — testing new ideas quickly and determining whether they are worth scaling
Technology
Depending on the project, you may work with technologies including:
Azure AI / Azure OpenAI · LangChain · Agentic AI / ReAct · RAG and Vector Stores · Python · SQL · REST APIs · React / JavaScript · Azure Services · Dayforce APIs and Integrations
Skills and experience we value:
- Enrolled in a Bachelor’s or Master’s program in Computer Science, Computer Engineering, Mathematics, Information Technology, or a related technical field
- Intermediate Python skills, including the ability to structure a codebase, work with APIs, and debug independently
- Intermediate SQL skills, including joins, aggregations, subqueries, basic data modelling, and query optimization
- Working knowledge of JavaScript and experience building or modifying UI components; React is a strong plus
- Understanding of LLM and generative AI fundamentals, including prompt design
- Strong analytical and problem-solving skills
- Ability to translate loosely defined business problems into technical approaches
- Comfort working in environments where requirements evolve as you learn
- Ability to prototype quickly while still thinking about maintainability, usability, and production readiness
- Curiosity and persistence to investigate how a process works before trying to automate it
- Strong communication skills and an ability to work directly with both technical and non-technical stakeholders
What would really make you stand out:
- Experience building full-stack applications or internal developer tools
- Experience with LangChain, Azure AI, Azure OpenAI, or agent frameworks
- Experience building RAG solutions or working with vector databases
- Experience integrating applications through REST APIs
- Experience with test automation tools such as Playwright, Selenium, or pytest
- Experience taking a project from initial idea through prototype to a usable application
- Exposure to HCM, payroll, workforce management, or Dayforce
- Previous internship, co-op, or project experience involving software engineering, AI, automation, or consulting
- A builder mindset: you enjoy understanding a problem, creating something useful, putting it in front of users, and improving it based on feedback