Manager, Applied AI

Invenergy•Chicago, IL

About The Position

The Manager, Applied AI (Enterprise Analytics & AI) is responsible for leveraging enterprise AI tools and platforms to design, build, and deploy practical AI solutions that deliver measurable business impact across the organization. This role works hands-on with individuals and teams to understand their needs, build low-code AI agents and other custom solutions, and enable teams to integrate AI into their workflows effectively and responsibly. This position serves as an organizational subject-matter expert on enterprise AI platforms, including their capabilities, limitations, and best practices. The role leads the co-development of AI agents and other AI solutions while fostering a culture of responsible AI use and self-sufficiency across the organization.

Requirements

Bachelor's degree in a technical or quantitative field such as computer science, information systems, engineering, data science, or a related discipline.
8+ years of experience within the industry or in a technology function, with significant achievements and upward growth.
Demonstrated experience designing, building, or managing AI agents or similar AI-driven solutions.
Strong familiarity with the Microsoft ecosystem, including Microsoft 365 and AI-enabled productivity tools.
Prior experience leading, mentoring, or managing direct reports, or demonstrated readiness to step into a people leadership role.
Ability to communicate complex technical concepts clearly to non-technical audiences, including presenting to senior leadership.
Strong independent time-management and project-management skills, with the ability to manage multiple initiatives simultaneously.
Proven ability to collaborate effectively across business, technical, and enablement teams.
High level of curiosity, enthusiasm for emerging technologies, and a continuous-learning mindset.

Nice To Haves

Experience managing employees in a technology function.
Direct, hands-on experience with Microsoft Copilot Studio, including designing and deploying enterprise AI agents or low-code AI solutions.
Experience supporting enterprise technology adoption, enablement, or change initiatives.
Experience developing or delivering technical training or learning content for broad employee audiences.
Familiarity with responsible AI practices, governance, security, or compliance considerations in an enterprise environment.
Experience partnering with data science, analytics, or engineering teams to translate advanced AI capabilities into user-facing solutions.
Exposure to Microsoft Power Platform, Azure AI services, Databricks, or related tools that complement enterprise AI solutions.
Proficiency in coding languages such as Python or SQL.

Responsibilities

Design, build, deploy and manage low-code AI agents and other complex custom AI solutions, such as multi-agent systems or advanced process automation, in partnership with business teams to address specific organizational needs and use cases.
Lead engagement with business teams in one-on-one and small-group settings to understand workflows, identify AI opportunities, and co-develop effective, responsible solutions.
Maintain deep familiarity with the full range of capabilities, limitations, and evolving features of the organization's enterprise AI platforms to ensure solutions are thoughtfully designed and maximize available functionality.
Oversee the evaluation of third-party AI software applications, assessing organizational fit, capability, security, and responsible AI considerations, and providing recommendations to inform Business Operations decisions.
Monitor and analyze organizational AI usage and adoption data; identify trends, gaps, and opportunities, and recommend targeted actions to improve utilization and impact.
Partner with the Talent Development team to design, deliver, and continuously improve training content and guidelines that help employees use AI tools effectively and responsibly and support self-service adoption across the organization.
Stay current on emerging AI capabilities and platform updates, proactively recommending features and solutions relevant to the organization's evolving needs.
Collaborate with Enterprise Analytics & AI data scientists, data engineers, and analytics teams to align end-user AI solutions with broader AI initiatives.
Manage one or more employees supporting AI adoption functions at the organization.