Senior Product Manager - Agentic Cloud | India

Position Overview

We are seeking a highly entrepreneurial, driven Senior Product Manager to take Five9's Agentic Data Cloud from its initial MVP to a scaled, market-defining platform. You will operate with the scrappy, startup-minded velocity you would bring to a 0-to-1 build, now applied to accelerating what works, ruthlessly cutting what does not, and expanding into the platform's next horizon.

You will own the full product lifecycle: sharpening the roadmap based on real customer feedback from the MVP, closing the gaps between what the platform does today and what enterprise contact centers need it to do, and laying the architectural and strategic groundwork for the capabilities that will define ADC's competitive position over the next two to three years.

You are comfortable operating in the space between early product and scaled platform—where the data is messy, the AI models have real limitations in production, and the right call is rarely obvious. You make decisions with incomplete information, you move fast without losing sight of quality, and you know when to double down versus when to change course.

Key Responsibilities

Strategic Vision & Execution

• Define and execute the product strategy for Five9's Agentic Data Cloud platform—spanning customer data unification, real-time contextual intelligence, AI-powered memory, behavioral analytics, and the data layer that powers intelligent agentic experiences across the contact center.

Navigate Ambiguity

• 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.

AI Native Product Thinking

• 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, without needing to build them yourself.

Cross-Functional Coordination

• Partner deeply with Engineering, AI, Design, and GTM functions to deliver superior products for our customers.

Customer-Centric Iteration

• 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.

Market Leadership

• Conduct competitive research and market analysis to identify new opportunities in Agentic Data Cloud evolution, agentic frameworks, and real-time data platform capabilities—and translate market signals into a differentiated roadmap that maintains a competitive edge across the full platform.

Ruthless Prioritization

• Demonstrate a builder's instinct with strong opinions, loosely held.
• In an AI-powered data platform context, this means knowing when to invest in data quality, model improvement, new capability, or UX guardrails—and possessing a track record of killing features or pivoting strategies that aren't delivering measurable outcomes for customers or the business.

Qualifications

Education

• Bachelor’s degree in Computer Science, Engineering, or a related field.
• An advanced degree in Engineering or a business discipline is a plus.

Professional Experience

• 4+ years of comprehensive professional experience in SaaS Product Management.
• The ideal candidate will demonstrate adaptability and success across both agile, high-growth startup environments and established enterprise organizations.

Product Leadership

• A proven track record in a formal Product Management capacity, successfully delivering B2B SaaS solutions.

Industry Expertise (Optional)

• Essential background in the Contact Center or Customer Experience (CX) industry coupled with direct experience building and shipping AI-driven products.

Technical Acumen

• 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.

Execution-Oriented

• A highly autonomous operator capable of driving initiatives forward without relying on extensive operational support structures.
• Must be able to articulate and defend strategic decisions effectively and collaboratively.

Critical Competencies

Applied AI Proficiency

• 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.

Data Product Instinct

• 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.

Operational Excellence

• 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.

Client Advocacy

• 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.