AI Product Owner

CGI•Lafayette, LA

8d•Onsite

About The Position

We are seeking an experienced AI Product Owner to manage and optimize enterprise AI products such as ChatGPT Enterprise, Microsoft Copilot, AI Agents, and other Generative AI solutions. The role will be responsible for defining the AI product roadmap, identifying business use cases, monitoring product adoption and KPIs, analyzing usage and cost trends, and continuously improving AI products to deliver measurable business value. The AI Product Owner will work closely with business, engineering, architecture, security, governance, and leadership teams to ensure AI products are scalable, cost effective, secure, and aligned with enterprise goals. This position is required in one of the following locations: Lafayette, LA, Knoxville, TN, Columbia, SC, Birmingham, AL

Requirements

5+ years of Experience as a Product Owner, Product Manager, or similar role managing enterprise technology products.
Good understanding of Generative AI, LLMs, RAG, AI Agents, and Agentic AI.
Experience with enterprise AI platforms such as ChatGPT Enterprise, Microsoft Copilot, Copilot Studio, or similar products.
Experience defining product roadmaps, backlogs, user stories, and priorities.
Strong understanding of AI product KPIs, adoption metrics, and usage analytics.
Understanding of LLM token usage, API consumption, model pricing, and AI cost optimization.
Experience creating dashboards and reports using tools such as Power BI or Tableau.
Understanding AI integrations, APIs, connectors, MCP servers, and AI gateways.
Familiarity with AWS, Azure, or other cloud AI platforms.
Understanding of enterprise security, governance, access controls, and Responsible AI.
Strong analytical, communication, and stakeholder management skills.
Ability to translate AI usage data and technical information into clear business insights for leadership.

Nice To Haves

Financial services or banking domain experience is preferred.
Relevant cloud or AI certifications such as AWS Certified Cloud Practitioner, AWS Solutions Architect, Microsoft AI Engineer Associate, or related certifications are preferred.

Responsibilities

Define and manage the AI product vision, roadmap, backlog, and priorities.
Identify and prioritize high value AI use cases across business teams.
Define and track AI product KPIs such as: User adoption and engagement, Active users and usage trends, Productivity improvements, Token and API consumption, Cost per user / application / use case, Business value and ROI.
Analyze AI product usage and provide descriptive insights to leadership.
Identify negative or abnormal usage patterns such as excessive token usage, unnecessary LLM calls, low value usage, and underutilized licenses.
Identify potential misuse or non compliant usage and coordinate with governance and security teams.
Recommend cost optimization techniques including: Model selection and model routing, Token reduction, Prompt optimization, Caching, Optimizing RAG and AI agent workflows, Reducing unnecessary LLM/API calls, AI license optimization.
Monitor AI platform costs and identify opportunities to reduce overall AI spending.
Create dashboards and executive reports for AI adoption, usage, cost, ROI, and product performance.
Gather feedback from users and continuously improve AI products and user experience.
Work with engineering teams to support AI agents, connectors, APIs, MCP servers, and enterprise integrations.
Ensure AI products follow enterprise security, governance, privacy, and Responsible AI standards.
Partner with business stakeholders to measure productivity gains and business outcomes from AI adoption.