ML Developer Sr – Data Agents

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 promise - Makes Work Life Better

TM - Reflects our commitment to employees, customers, partners and communities globally.

We are looking for a Senior Software Developer to join the team building AI Agent capabilities in Dayforce, with a focus on data‑centric agents. This role is ideal for someone who can design, build, and ship production‑quality agent systems—including a natural language to SQL (NL2

SQL) solution—using modern agent frameworks (Lang Chain, Lang Graph, Python) and AI development tools (Copilot, Claude, Git Hub Copilot Agents, IDE agents, and internal agents). The goal is to accelerate delivery while maintaining high standards for quality, security, and operational excellence.

This is a high‑impact role. You will help transform how millions of users across 150+ countries interact with Dayforce by enabling natural language access to data and automating complex data workflows through intelligent agents. You will work across the full software lifecycle—architecture, design, prototyping, implementation, testing, release, and production operations—and partner closely with product, platform, and engineering teams.

• Design, build, and maintain data‑centric AI agents, including an NL2
  
  SQL solution that translates natural language queries into accurate and performant SQL against complex enterprise data models
• Develop agent architectures using Lang Chain, Lang Graph, and Python, including tool use, multi‑step workflows, and structured reasoning patterns
• Build robust evaluation, testing, and observability patterns to ensure correctness, reliability and safety of agent outputs
• Design and implement guardrails, validation layers, and sandboxed execution environments to safely run generated SQL and agent‑produced code in production
• Continuously improve agent accuracy and relevance through prompt engineering, fine‑tuning strategies, and feedback loops

• Design and implement new microservices, evolve existing services, and build or consume well‑designed APIs to support agent and data workflows
• Own critical areas of the agent codebase and provide technical stewardship for shared patterns and libraries
• Improve performance, relevance, and reliability of data agent services through profiling, tuning, and iterative optimization
• Build tooling and automation around releases, integrations, and operational workflows and contribute to long‑term improvements in production support, incident learnings, reliability, and operational maturity

• AI‑assisted scaffolding with rigorous human review
• AI‑generated test suites and regression harnesses
• Fast refactoring and modernization supported by automated verification
• Agentic workflows for repetitive engineering tasks such as migrations, API clients, documentation, and runbooks
• Secure and responsible AI usage with strong review discipline, no sensitive data leakage, and traceable change sets

• Partner with product and engineering stakeholders to understand data access needs and translate them into agent‑driven solutions
• Translate business requirements into clear, well‑reasoned technical designs
• Present system designs and complex technical topics to both technical and non‑technical audiences
• Mentor peers through pairing, coaching, and high‑quality code and design reviews
• Take an organization‑first approach to accountability, prioritizing business outcomes over individual ownership

• Strong Python development experience with a proven track record of building production systems
• Hands‑on experience building agents using Lang Chain, Lang Graph, or comparable frameworks, including…