Senior AI Engineer

Xcel Energy•Minneapolis, MN

2d•$130,000 - $170,000•Onsite

About The Position

The Sr. AI Engineer plays a pivotal role in advancing Xcel’s AI vision by leading the technical delivery of innovative IT and AI-powered solutions that drive strategic value and operational excellence. This role empowers teams to leverage emerging AI capabilities such as agentic patterns, generative AI developer tooling, and secure orchestration to deliver innovative solutions that transform business operations. In addition to technical leadership, the Sr. AI Engineer will mentor and guide teams in adopting AI tooling, establish best practices, foster a culture of continuous improvement and collaboration and ensure that AI solutions are secure, scalable, and aligned with enterprise goals. The position partners with Architecture, Security, and Operations teams to integrate enterprise architecture, compliance, and operational requirements into every solution. The Sr. AI Engineer is responsible for leading technical aspects of IT solution delivery, strategic planning, and operational excellence. They are responsible for managing the overall health of the technology ecosystem and will manage and oversee design of solutions to meet business needs and support the overall IT Strategy. They provide technical guidance in partnership with Architecture and cross-organizational input and in accordance with business unit objectives. They are a consultant to business managers, architecture, security and operations teams to drive cross-awareness of business needs and opportunities. They bring innovative solutions to the business line by leveraging their technical expertise. They identify and implement continuous improvement over cost, security, operation, and functionality of the solutions in their domain.

Requirements

Solid grasp of core AI engineering concepts, including agentic patterns, agent-to-agent (A2A) communication, tool use, and orchestration.
Hands-on experience with generative AI developer tooling such as Claude Code, OpenAI Codex, GitHub Copilot, or comparable coding agents, including day-to-day use in a professional development workflow.
Proficiency building with AI-relevant languages and ecosystems, particularly TypeScript, Python, and .NET.
Working knowledge of the Model Context Protocol (MCP) and experience with related frameworks and SDKs (e.g., FastMCP, Microsoft Agent Framework, or equivalents).
Demonstrated experience building agents, skills, hooks, plugins, and tool integrations that extend AI platforms.
Bachelor's degree in Technology, Science, Business or related field, or 4 years of experience equivalent to the position.
Ten years of related functional experience.
Excellent communication skills, effective with varying organizational levels and skill set, and able to translate between technical and non-technical concepts.
Excellent Relationship Management and collaboration skills, with a track record of working as one team cross-organizationally to drive inovation and business results.
Expertise managing the lifecycle of technical solutions.
Deep Subject Matter Expertise within the respective system domain products, platforms, processes and architecture.
Broad and deep knowledge of technology architecture, infrastructure, network, security and software principles and models.
Experience working in partnership with internal and external vendors.
Excellent analytical, problem-solving and troubleshooting skills.
Extensive knowledge of future technology trends within area of expertise.
Demonstrated leadership on technical aspects of large scale projects.
Experience coaching other developers in system deployment or operational troubleshooting.
Experience with delivery methodologies (Waterfall, Agile, Scrum) and operational models (ITIL).
Experience and understanding of core IT Service Management functions, such as Change Management and Incident Management.

Nice To Haves

Familiarity with AI security and governance controls — approval flows, guardrails against unapproved actions, plugin/tool allowlisting, sandboxing, and permission models.
AI Identity and data access patterns — OAuth, scoped tokens, and least-privilege access for agents acting on behalf of users (Microsoft Graph, enterprise APIs, etc.).
Mentorship and technical leadership — guiding teams adopting AI tooling, establishing patterns, and reviewing AI-generated code at scale.

Responsibilities

Lead and support solution lifecycle technical activities.
Ensure solutions are designed for great user experience and operational performance.
Lead design, ensuring Enterprise Architecture, Security, Operations and Compliance aspects are continuously integrated into solutions.
Provide input to cost and schedule estimation.
Responsible for overall integrity of system design and operation.
Oversee vendor activities.
Conduct peer reviews and approve system changes and technical solution design.
Coach and mentor less experience team members.
Partner cross-organizationally to drive minimal costs on optimal solutions.
Provide in-depth technical information to stakeholders as needed.
Innovate through usage of industry emerging capabilities and evolving customer needs.
Provide input to strategic roadmap and technical dependencies.
Continuously stay current on, and apply, technical industry knowledge pertaining to the respective domain.
Review solution performance, and continually assess health of systems.
Track and drive awareness to operational and technical debt risks.
Provide escalated support to incident and problem management.
Utilize analytics to improve availability, reliability, efficiency and capacity.