AI Systems Engineering Manager - HRIS

• Lead, coach, and develop a team of engineers, providing technical guidance, career development support, and ongoing performance feedback
• Set the engineering vision, roadmap, and execution strategy for HRIS platforms in alignment with organizational goals and enterprise architecture standards
• Modernize legacy platforms through automation, cloud enablement, improved engineering practices, and scalable platform design
• Guide the full engineering lifecycle including requirements definition, architecture, implementation, release, support, and continuous improvement
• Drive platform engineering practices including infrastructure as code, CI/CD, observability, resiliency, and secure-by-design delivery
• Partner with HR, security, infrastructure, architecture, delivery, data, and enterprise platform teams to align technical solutions with business needs
• Build team capability in automation, scripting, cloud deployment, modern platform tools, and engineering best practices
• Implement and continuously improve performance management processes for the team, including goal setting, regular reviews, development planning, and accountability for results
• Develop and manage plans, priorities, resource allocation, and execution risks to ensure initiatives are delivered on time and with high quality
• Identify, assess, and mitigate technical and operational risks while driving pragmatic solutions to complex engineering challenges
• Ensure platforms are secure, stable, scalable, well governed, and compliant with company standards and security requirements
• Communicate effectively with technical and non-technical stakeholders, translating complex concepts into clear and actionable decisions

• Bachelor's degree in Engineering, Computer Science, Information Technology, or a related field, or equivalent practical experience
• Experience leading technical teams in systems engineering, platform engineering, enterprise applications, infrastructure engineering, or HR technology environments
• Experience setting technical direction, driving delivery, and developing engineering talent
• Strong experience designing and implementing solutions for complex enterprise platforms
• Experience leading modernization efforts involving automation, cloud enablement, and legacy transformation
• Experience with infrastructure as code, cloud deployment, scripting, and CI/CD tools
• Strong knowledge of security practices including RBAC, secrets management, patching, vulnerability remediation, SSO, and SAML
• Strong communication, problem-solving, analytical, and cross-functional collaboration skills
• Proven ability to lead through ambiguity, influence stakeholders, and align teams around a common technical direction
• Working knowledge of Artificial Intelligence (AI) and Machine Learning (ML) concepts, including supervised and unsupervised learning, model lifecycle, and data pipelines
• Experience integrating AI-driven capabilities into enterprise platforms, such as intelligent automation, predictive insights, conversational interfaces, decision-support tools, or workflow augmentation
• Familiarity with AI-enabled platforms and tools, including cloud-based AI services, large language models, intelligent process automation, analytics platforms, or similar emerging technologies
• Ability to partner with data science, analytics, and platform teams to translate business needs into AI-enabled platform requirements, architectures, and practical use cases
• Understanding of data pipelines, data governance, and data quality practices required to support responsible and scalable AI solutions
• Understanding of model risk management and ethical AI considerations, including bias, transparency, explainability, privacy, and security
• Experience applying AI to improve engineering productivity, platform operations, monitoring, testing, support workflows, or service reliability
• Ability to evaluate AI opportunities pragmatically and drive adoption in ways that improve outcomes, reduce manual effort, and strengthen platform capability

• Experience with HRIT, HRIS, Workday, or other enterprise business systems
• Experience leading platform modernization, cloud migration, and automation adoption
• Familiarity with DataDog, OpenTelemetry (OTEL), GitHub, or similar engineering tools
• Experience with enterprise integration patterns, APIs, and modern platform architectures
• Experience leading teams through technology modernization and AI adoption initiatives
• Master's degree in Engineering, Computer Science, Data Science, Information Technology, or a related technical field

Relocation benefits may be eligible