CI360 AI & Agentic AI Product Manager at SAS, Cary HQ, NC
CI360 AI & Agentic AI Product Manager at SAS in Cary HQ, NC. Est. up to $200k. Apply with swipeandhired.
Job Category
Research and Development
Hiring Manager
Rob Taylor
Employee Referral Bonus
Tier 2
Recruiter
Cory Craig
Position Type
Professional
CI360 AI & Agentic AI Product Manager - Hy brid | Cary, North Carolina
We’re a leader in data and AI. Through our software and services, we inspire customers around the world to transform data into intelligence - and questions into answers.
If you're looking for a dynamic, fulfilling career with flexibility and a world-class employee experience, you'll find it here. We're recognized around the world for our inclusive, meaningful culture and innovative technologies by organizations like Fast Company, Forbes, Newsweek and more.
About the job
We are seeking a CI360 AI & Agentic AI Product Manager to define and lead the agentic AI strategy for CI360, with a focus on making marketers more efficient and effective across the full marketing lifecycle. This role will shape how AI agents, multi-agent workflows, and MCP-enabled capabilities can support marketers from audience creation and customer journey design through to insight generation, campaign execution, and performance optimization.
The successful candidate will identify high-value AI and agentic use cases within CI360, translate customer and market needs into product strategy, and work closely with other product managers, engineering, data science, UX, architecture, and go-to-market teams to deliver differentiated capabilities that improve marketer productivity, decision quality, and campaign outcomes.
This role is critical to evolving CI360 into an AI-enabled marketing platform that helps customers reduce manual effort, accelerate campaign creation, improve personalization, and continuously optimize marketing performance.
As an AI & Agentic AI Product Manager , you will:
- Define the CI360 agentic AI product strategy across MCP, AI assistants, autonomous workflows, and multi-agent concepts that support the end-to-end marketing lifecycle.
- Develop product requirements and roadmap priorities for agentic AI capabilities grounded in customer needs, market trends, business impact, and technical feasibility.
- Lead product discovery with customers, marketers, sales, customer advisory teams, and internal stakeholders to understand pain points, use cases, adoption barriers, and measurable outcomes. Utilize rapid prototyping techniques to validate ideas and drive adoption of AI and Agentic AI solutions that improve marketer productivity and business outcomes.
- Ensure AI capabilities are trustworthy, explainable, governed, and aligned with enterprise expectations, including transparency, human-in-the-loop controls, auditability, and responsible AI principles.
- Define success measures for AI and agentic features, including marketer productivity gains, campaign cycle-time reduction, recommendation adoption, customer satisfaction, usage, and business impact.
Required Qualifications
- 5+ years of experience in product management experience in a SaaS, marketing technology, customer intelligence, analytics, AI, or enterprise software environment.
- Experience with AI, generative AI, agentic AI, AI assistants, orchestration patterns, or multi-agent concepts.
- Strong customer discovery skills, with the ability to validate customer pain points and prioritize capabilities based on value, feasibility, and strategic fit.
- Ability to translate ambiguous AI and agentic concepts into clear product requirements, user experiences, and delivery priorities.
- You’re curious, passionate, authentic and accountable. These are our values and influence everything we do.
Preferred Qualifications
- Strong understanding of marketing workflows, including audience management, segmentation, journey orchestration, campaign execution decisioning, insight generation, and performance optimization.
- Familiarity with MCP, AI agents, tool-calling architectures, multi-agent orchestration, or enterprise AI integration patterns.
- Understanding of responsible AI, model governance, explainability, privacy, and enterprise trust requirements.
- Experience bringing early-stage or emerging technology concepts from discovery through productization.
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