Agentic Engineer

About the Opportunity

At Dayforce, we are transforming Powerpay, our Canadian payroll and human capital management solution, by leveraging modern cloud-native technologies and Artificial Intelligence to build smarter, more efficient applications.

We are looking for a passionate, hands-on AI Software Engineer specializing in Agentic AI who combines strong software engineering fundamentals with practical experience developing AI-powered applications and intelligent agents.

You will contribute to designing and building AI agents, automating complex workflows, and integrating Large Language Models (LLMs) into enterprise applications.

We value engineers who are curious, innovative, and capable of transforming emerging AI technologies into practical, reliable, and scalable solutions that deliver real business value.

What You'll Get to Do

Design, develop, test, and maintain AI-powered applications and intelligent agents.

Build agentic workflows capable of executing multi-step tasks, interacting with tools, and automating business processes.

Integrate LLMs with enterprise applications, REST APIs, databases, and external services.

Develop AI solutions using frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent technologies.

Implement Retrieval-Augmented Generation (RAG) to enable AI applications to retrieve and use enterprise knowledge.

Apply prompt engineering, context management, and tool-calling techniques to improve AI agent capabilities.

Develop reusable backend services and components supporting AI-powered applications.

Evaluate AI-generated outputs and improve agent accuracy, reliability, performance, and security.

Collaborate with developers, architects, Product Owners, and QA engineers to identify opportunities for AI-driven automation.

Deploy and maintain AI-powered services within cloud-native environments.

Experiment with emerging AI technologies and contribute to continuous improvement of AI engineering practices.

Skills and Experience We Value

Software Engineering

Strong hands-on programming experience with Python, Java, TypeScript, or equivalent languages.

Experience developing backend services, RESTful APIs, and enterprise applications.

Solid understanding of software engineering principles, object-oriented programming, and design patterns.

Good knowledge of databases, API integration, and distributed application concepts.

Experience with Git, automated testing, and Agile development practices.

Familiarity with AWS or equivalent cloud platforms.

Strong debugging, analytical reasoning, and problem-solving skills.

AI and Agentic Development

Practical experience integrating LLMs such as OpenAI GPT, Claude, or equivalent models into applications.

Understanding of agentic AI concepts, including tool calling, workflow orchestration, planning, and context management.

Experience with AI frameworks such as LangChain, LangGraph, Semantic Kernel, or equivalent tools.

Knowledge of prompt engineering, structured outputs, and LLM API integration.

Understanding of Retrieval-Augmented Generation (RAG), embeddings, and vector databases.

Ability to design AI agents that interact with APIs, databases, and external tools.

Understanding of LLM limitations, hallucinations, and techniques for improving AI application reliability.

Engineering and Collaboration

Ability to independently investigate technical challenges and implement practical solutions.

Strong analytical thinking and willingness to experiment with emerging technologies.

Ability to translate business requirements into working AI-powered solutions.

Good communication and collaboration skills.

Strong sense of ownership, accountability, and continuous learning.

AI Engineering and Responsible AI

At Dayforce, we encourage engineers to explore innovative applications of AI while maintaining high standards of software quality, security, and reliability.

We are interested in candidates who can:

Design AI agents that execute meaningful tasks and automate workflows beyond traditional conversational AI.

Apply effective prompt engineering and context management to improve agent performance.

Evaluate and validate AI-generated outputs through testing and appropriate evaluation techniques.

Implement safeguards, access controls, and human approval mechanisms where required.

Design solutions that manage AI-related risks, including inaccurate responses, unintended actions, and sensitive data exposure.

Consider performance, latency, token usage, and operational costs when building AI-powered applications.

Follow organizational policies for responsible AI usage, information security, and data protection.

What Success Looks Like

You will be a hands-on AI Software Engineer capable of independently developing AI-powered applications and intelligent agents that solve real business problems.

You will demonstrate strong software engineering fundamentals, practical knowledge of LLMs, and the ability to design secure, reliable, and maintainable agentic workflows.

You will contribute to Powerpay's AI innovation journey by building intelligent solutions that improve productivity, automate business processes, and enhance user experiences.

Most importantly, you will go beyond AI experimentation to deliver working solutions that create measurable business value.