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OpenAI's People Systems team is seeking a Workday Engineer to design, build, and operate the technical infrastructure powering HR, recruiting, payroll, benefits, and performance operations at scale. This is a highly technical role combining deep Workday expertise with strong software engineering fundamentals.
You will design and maintain Workday integrations, applications, and workflow automations across payroll, benefits, recruiting, performance, and case management domains. Key responsibilities include improving reliability and scalability of People systems through rigorous engineering practices, building technical solutions that connect Workday with internal platforms and external vendors, and contributing to agentic internal workflows that combine HR data, automation, and AI-powered tooling.
The role requires comfort going beyond configuration work—you'll reason through ambiguous systems problems, write and debug technical solutions, work in Git-based environments, and use modern developer workflows including CLI-driven tooling. You'll partner closely with cross-functional teams across People, Finance, Security, and Engineering to build secure, scalable, and practical systems.
Ideal candidates have 5-10 years of experience in Workday engineering, integrations, or platform automation, with strong hands-on expertise in Workday technologies (EIB, Studio, Cloud Connect, Extend, reporting, calculated fields, security, business process design). You should have a track record of building technical solutions beyond administration, including automation, scripting, debugging, and systems design. Git fluency, CLI-based workflow comfort, and experience designing production integrations with high reliability and security standards are essential.
Nice-to-have skills include experience integrating Workday with finance systems, identity platforms, recruiting tools, case management, or internal developer platforms; observability and alerting expertise; internal tools and automation framework development in high-growth environments; and familiarity with secure systems design for sensitive employee data.
