Senior Product Manager – Agentic Cloud

Role Overview

• Define and execute the product strategy for Five9's Agentic Data Cloud platform.
• Handle real-world complexity across contact center data ecosystems—manage limitations of LLMs, vector retrieval, real-time pipelines, identity resolution, and AI inference in production environments, and make critical product decisions even when model behavior is non-deterministic or customer data is inconsistent across sources.
• Translate AI and ML capabilities—including retrieval-augmented generation, semantic understanding, real-time inference, and predictive analytics—into platform features that solve concrete CX problems.
• Know enough about how models and data pipelines work to have credible technical conversations with Applied Science and Engineering.
• Partner deeply with Engineering, AI, Design, and GTM functions to deliver superior products for our customers.
• Actively engage with customers and design partners to gather feedback, validate assumptions, and refine the product roadmap based on real-world usage and pain points.
• Conduct competitive research and market analysis to identify new opportunities in Agentic Data Cloud evolution, agentic frameworks, and real-time data platform capabilities.
• Demonstrate a builder's instinct with strong opinions, loosely held.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• 4+ years of comprehensive professional experience in SaaS Product Management.
• A proven track record in a formal Product Management capacity, successfully delivering B2B SaaS solutions.
• Essential background in the Contact Center or Customer Experience (CX) industry coupled with direct experience building and shipping AI-driven products.
• Deep understanding of the product development lifecycle for data and AI-driven solutions, including data ingestion, unification, real-time pipeline architecture, model integration tradeoffs, and how clean, well-structured data translates into reliable AI outputs.
• A highly autonomous operator capable of driving initiatives forward without relying on extensive operational support structures.
• Practical experience shipping AI-powered products—not as a supporting feature but as a core part of the value proposition.
• You understand how LLMs, ML models, and AI pipelines behave in production, including their failure modes, and you have made product decisions that account for that reality rather than assuming ideal model behavior.
• You have owned or significantly contributed to a data product—something that ingests, processes, enriches, or acts on data to deliver value to end users or downstream systems.
• You understand the trade-offs between data freshness, accuracy, and performance, and you know that the hardest problems in data products are rarely technical in isolation—they are technical and organizational at the same time.
• A strong bias for action with a track record of translating ambiguous platform strategy into shipped, adopted product.
• You can hold near-term delivery commitments and long-horizon roadmap bets simultaneously without letting either become an excuse for the other.
• A genuine commitment to staying close to customers throughout the product lifecycle—not just at discovery.
• You recruit beta customers, run structured feedback cycles, and bring specific, actionable signal back into roadmap decisions.
• Customer engagement is a core part of how you work, not something you delegate.

Tech Stack

• Cloud

Benefits

• Health insurance
• Professional development opportunities