Lead Business Process Analyst

Why UKG:  

At UKG, the work you do matters. The code you ship, the decisions you make, and the care you show a customer all add up to real impact. Today, tens of millions of workers start and end their days with our workforce operating platform. Helping people get paid, grow in their careers, and shape the future of their industries. That’s what we do.

We never stop learning. We never stop challenging the norm. We push for better, and we celebrate the wins along the way. Here, you’ll get flexibility that’s real, benefits you can count on, and a team that succeeds together. Because at UKG, your work matters—and so do you.

ROLE SUMMARY
This is a pooled hiring role for the AI Automation Incubator — a cross-functional team responsible for discovering, designing, building, deploying, and scaling intelligent automation solutions across enterprise workflows.
Rather than hiring into a single narrow function, this role brings together complementary capabilities across process analysis, automation engineering, applied AI/ML, data measurement, and change enablement. Candidates will contribute based on their strengths while collaborating across the full automation lifecycle.
The goal is not just efficiency — but maximizing human contribution. Every workflow is designed with human judgment, human override, and role elevation in mind.
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CORE RESPONSIBILITIES
Operational Leadership with AI
• Lead day-to-day work using AI as a core operational layer — not as an add-on tool
• Apply AI to structure thinking, accelerate analysis, and improve decision quality
• Identify where AI augments human judgment vs. introduces risk
• Set standards for responsible AI use: transparency, validation, and override
• Continuously translate emerging AI capabilities into practical workflow improvements
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1. Work Design
• Lead the organization through transformational work design — redefining how work should operate, not documenting how it currently works
• Challenge legacy workflows, assumptions, and handoffs that no longer serve speed, quality, or human contribution
• Partner with business leaders to identify structural constraints in current operating models and redesign them at the root
• Define future-state workflows that intentionally rebalance automation and human judgment
• Establish clear principles for what should be automated, augmented, or protected as expertise
• Drive alignment on redesigned workflows before any build begins — ensuring the team is not scaling broken processes
• Ensure all designs reflect the core principle: maximizing human contribution alongside automation
2. Automation Development & Integration
• Build and configure automation workflows using platforms such as UiPath, Power Automate, Make, or similar
• Integrate workflows with enterprise systems (CRM, ERP, HRIS, data platforms) via APIs and webhooks
• Implement human-in-the-loop checkpoints, override mechanisms, and escalation paths
• Monitor and maintain automation reliability, uptime, and performance
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3. AI / ML Enablement
• Evaluate where AI/ML improves automation quality or coverage
• Integrate intelligent components (LLMs, NLP, document processing, classification models)
• Define confidence thresholds and fallback logic for safe human intervention
• Monitor model performance, drift, and reliability in production
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4. Measurement & Insights
• Design baseline and pilot measurement frameworks
• Track metrics: processing time, error rates, throughput, override frequency
• Analyze human contribution metrics (freed capacity, role elevation)
• Build dashboards to inform scaling decisions
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5. Change Management & Enablement
• Support onboarding and training for automation deployments
• Communicate system behavior, human roles, and override responsibilities
• Collect qualitative feedback via interviews and surveys
• Drive adoption through structured communication and stakeholder engagement
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6. Cross-Functional Delivery & Ownership
• Translate business requirements into workflows and implementation plans
• Collaborate across roles from discovery through pilot and scale
• Support documentation, testing, and operational readiness
• Contribute reusable patterns and best practices
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WHAT WE’RE LOOKING FOR
• 3–6 years of experience in:
o Process analysis
o Automation engineering
o Data analysis / BI
o Applied AI/ML
o Change management
• Strong ability to structure ambiguous problems
• Experience with automation tools and API