Senior Product Manager - AI

the opportunity to help shape AI products in a proven enterprise software company with real customer problems, strong leadership commitment, and the tools to move quickly, Varicent is a great place to build. Key Responsibilities As a Senior Product Manager, AI Strategy , you will drive the 0-to-1 strategy, incubation, and roadmap for new AI products, agents, and capabilities. This is a senior individual contributor role created to ensure Varicent's AI capabilities are grounded in high-value customer problems, shaped into clear product strategies, and brought from early concept through incubation and validation. You will work closely with customers and internal teams to turn ambiguous opportunities into well-defined AI products, agents, and capabilities that can deliver measurable customer and business value. You will partner closely with Product, Product Operations, Engineering, Design, Product Marketing, Go-to-Market, Customer Success, Sales, Support, and customers to bring AI-powered capabilities from discovery through validation, launch, and scale. This role is ideal for a product leader who is comfortable working in ambiguity, deeply curious about AI, and motivated by building products that create measurable customer and business impact. Responsibilities Own the AI product strategy and roadmap: Own the end-to-end product roadmap across new and existing AI capabilities, agents, and product experiences. Prioritize investments based on customer value, business impact, adoption feedback, technical feasibility, data readiness, and strategic differentiation. Lead discovery for prioritized opportunities: Validate high-value customer problems and identify where AI can meaningfully improve decision-making, productivity, or operational outcomes. Engage in customer research, evaluate market trends, understand the competitive landscape, and analyze product usage data to shape clear opportunity areas. Translate opportunities into product requirements: Convert prioritized AI opportunities into clear product requirements, PRDs, and MVP definitions. Define AI evaluation and success criteria: Define what success looks like for new AI products before they enter customer validation, working closely with the AI Adoption & Customer Value Product Manager to establish evaluation criteria. Partner with Engineering and Design through early delivery: Work closely with Engineering and Design to understand feasibility, data dependencies, implementation tradeoffs, model behavior, system constraints, and risks. Provide product leadership throughout early delivery to keep teams focused on customer outcomes and validation goals. Prepare AI products for customer validation, launch, and scale: Partner with the AI Adoption & Customer Value Product Manager to ensure new AI products are designed for successful transition from incubation to customer deployment, go-to-market readiness, adoption, and scale. Incorporate customer readiness, enablement needs, feedback loops, and value realization considerations early in the product development process. Partner with Product Marketing and Go-to-Market teams: Work closely with Product Marketing and Go-to-Market teams to shape positioning, messaging, launch strategy, enablement materials, customer-facing assets, and internal readiness for new AI capabilities. Ensure product value, differentiation, customer outcomes, and adoption paths are clearly communicated across internal and external audiences. Use analytics and customer feedback to inform roadmap decisions: Leverage product analytics, customer feedback, go-to-market insights, adoption data, usage patterns, and deployment learnings to understand how AI products are performing. Use these insights to refine product priorities, improve product quality, and guide future roadmap decisions. Drive cross-functional alignment: Collaborate with Product, Engineering, Design, Go-to-Market, Product Marketing, Customer Success, Support, and leadership to align AI product initiatives to customer and business outcomes. Communicate product strategy, roadmap priorities, opportunity assessments, and tradeoff decisions across the business. Influence priorities and foster collaboration across teams without direct authority. Stay ahead of AI product trends: Build a strong product perspective on AI agents, autonomous workflows, MCPs, agent orchestration, AI evaluation, and enterprise AI governance. Translate emerging AI trends into practical product opportunities and help the broader product team understand where AI can create meaningful workflow value. Knowledge, Skills & Experience 8–10+ years of professional experience, including 6+ years in Product Management, preferably in B2B SaaS, enterprise software, AI, automation, or data-driven products. Bachelor's degree in Business, Computer Science, Engineering, or a related field required. Proven experience in a senior individual contributor role owning product strategy and roadmap for new products, defining products from 0-to-1, including discovery, opportunity validation, MVP definition, PRD creation, early delivery, and customer validation. Strong familiarity with emerging AI concepts such as autonomous agents, MCPs, agent orchestration, AI evaluations, enterprise AI governance, trust, explainability, and responsible AI practices. Proven ability to translate ambiguous customer and business problems into clear product strategies, requirements, success criteria, and delivery plans. Strong analytical and strategic thinking skills, with the ability to combine customer insight, market trends, product data, technical considerations, and commercial context into clear recommendations. Skilled at using data, experimentation, and prioritization frameworks such as RICE, ROI, and Value vs. Effort to focus teams on the highest-impact initiatives. Demonstrated ability to partner closely with Engineering, Design, Product Operations, Product Marketing, Customer Success, and Go-to-Market teams. Deep understanding