AI Workflow Automation Lead

The Enterprise Risk AI Workflow Automation Lead is a senior individual contributor responsible for turning a substantial share of Enterprise Risk work into scalable AI-enabled operating models. The role translates strategic intent, objective-state designs, and early proof-of-concept work into governed solutions that improve cycle time, consistency, traceability, and organizational reach., * Workflow Transformation: Convert current-state Enterprise Risk processes, target-state operating concepts, and early prototypes into backend AI workflows that reduce manual effort and increase departmental throughput.

• Enterprise Risk System Integration : Define and implement interactions between agentic workflows and internal systems, including document repositories, workflow and ticketing tools, reporting solutions, structured data sources, knowledge repositories, and approved plugins or connectors that extend AI workflows into enterprise tools and content environments.
• LLM API & Tool-Calling Design : Translate business workflow needs into implementation requirements involving LLM APIs, approved plugins and connectors, selected internal and external APIs, structured data exchange, tool-calling patterns, permissions, logging, and safe execution boundaries. Partner with technical teams when deeper engineering support is needed.
• Human / AI Boundary & Handoff Design: Establish the design for human and AI interaction, create protocols for review points, approval gates, exceptions, escalation, and accountability, define expectations for human oversight, and periodically update those patterns as technology and tools evolve.
• AI Boundary Forecasting : Continuously evaluate what current AI tools can reliably automate, document failure patterns, and forecast where practical capability boundaries may move over the next three to six months, so implementation plans stay aligned with the next wave of usable functionality.

• Bachelor's degree in business, analytics, information systems, computer science, operations, engineering, economics, or a related discipline;
• Or Seven years of an equivalent combination of education and relevant experience.
• Relevant experience implementing AI-enabled workflows, agentic systems, automation solutions, enterprise knowledge workflows, or adjacent process-transformation capabilities in a business environment.
• Working knowledge of LLM model APIs, approved plugin and connector integration patterns, authentication and permissions concepts, structured and unstructured data exchange, and safe execution controls for agentic workflows.
• Demonstrated ability to establish human and AI operating boundaries, create protocols and expectations for handoffs and review, and update those protocols as capabilities evolve.
• Ability to assess current AI capability boundaries, recognize material failure modes, and translate a three-to-six-month capability outlook into a staged implementation roadmap.

Preferred Requirements

• Experience designing or operating multi-step agentic workflows that retrieve information, reason over data, call APIs or tools, and generate auditable outputs across enterprise environments.
• Experience with AI evaluation, testing harnesses, prompt and version management, failure-mode documentation, model or agent monitoring, and human-in-the-loop quality assurance.
• Experience interfacing AI workflows with internal systems such as document management platforms, workflow or ticketing tools, enterprise knowledge retrieval solutions, reporting environments, structured data sources, and approved plugins or connectors that support enterprise workflow execution.
• Experience writing Python automation scripts or moderate-complexity internal code to support AI workflow orchestration, tool calling, or prototype-to-production implementation.
• Familiarity with Microsoft enterprise tooling such as Power Platform, Power Automate, Power BI, Copilot, related plugin or connector ecosystems, or comparable enterprise AI and automation ecosystems.
• Experience creating operating protocols, review expectations, or implementation standards for human and AI collaboration in controlled environments.
• Experience within Enterprise Risk Management, Compliance, Internal Audit, Controls, Governance, utilities, energy, or another highly regulated environment.
• Understanding of AI governance and risk management frameworks.

The anticipated starting base pay for this position is: $112,200.00 to $159,400.00 per year

This position is eligible for the following benefits: Annual Incentive Program, Medical/Pharmacy Plan, Dental, Vision, Life Insurance, Dependent Care Reimbursement Account, Health Care Reimbursement Account, Health Savings Account (HSA) (if enrolled in eligible health plan), Limited-Purpose FSA (if enrolled in eligible health plan and HSA), Transportation Reimbursement Account, Short-term disability (STD), Long-term disability (LTD), Employee Assistance Program (EAP), Fitness Center Reimbursement (if enrolled in eligible health plan), Tuition reimbursement, Transit programs, Employee recognition program, Pension, 401(k) plan, Paid time off (PTO), Holidays, Volunteer Paid Time Off (VPTO), Parental Leave

Benefit plans are subject to change and Xcel Energy has the right to end, suspend, or amend any of its plans, at any time, in whole or in part.

In any materials you submit, you may redact or remove age-identifying information including but not limited to dates of school attendance and graduation. You will not be penalized for redacting or removing this information.

As a leading combination electricity and natural gas energy company, Xcel Energy offers a comprehensive portfolio of energy-related products and services to 3.4 million electricity and 1.9 million natural gas customers across eight Western and Midwestern states. At Xcel Energy, we strive to be the preferred and trusted provider of the energy our customers need. If you're ready to be a part of something big, we invite you to join our team.