Senior/Principal Product Manager

RingCentral•Belmont, CA

2d•$174,000 - $212,200

About The Position

RingCentral is seeking a Senior/Principal Product Manager to define and ship the platform layer for AI agents. This role involves owning the agentic platform, developer platform, evaluation and model operations, and customer engagement outcomes. The ideal candidate will have experience in enterprise conversational and agentic AI, with a track record of shipping impactful products. You will be responsible for strategy documents, customer engagement, and cross-functional partnerships. This is a critical role in shaping the future of AI-powered business communications at a rapidly growing company.

Requirements

Seven or more years in product management with a track record of company-level impact for Principal, including at least two years owning conversational AI, agentic AI, or ML-powered products in production.
Shipped an LLM-based product to real users at scale (production traffic, on-call rotation, consequences for errors).
Technical fluency to be a counterpart to engineering (reason about prompting, context management, retrieval, tool/function calling, latency/token budgets, fine-tuning vs. prompting, architectural choices).
Platform product experience (owned APIs, SDKs, or extensibility surfaces for developers/technical administrators, understanding of versioning and backward compatibility).
Enterprise B2B SaaS depth (navigated security reviews, procurement, admin/permission models, audit requirements, understanding of buyer/administrator/user distinctions).
Quantitative rigor (define success metrics before building, instrument them, use data to inform decisions, comfortable in SQL or equivalent).
Excellent written communication (writing sample required).
A bachelor's degree in a technical, quantitative, or design field, or equivalent practical experience.

Nice To Haves

Direct experience at a conversational AI, agentic AI, or CCaaS and CX automation company (AI agent platform, agent-assist product, enterprise agent builder) where AI agent quality was personal accountability.
Hands-on voice AI experience (real-time streaming, sub-second latency budgets, ASR/TTS selection, telephony realities).
Experience building or owning an evaluation harness for non-deterministic systems.
Forward-deployed or solutions-adjacent experience (personally stood up an AI agent in a customer environment and owned the outcome).
Conversation design background or credible collaboration with conversation designers.
Contact center domain knowledge (routing, WEM, QA, VP of Customer Care metrics).
Familiarity with AI governance landscape (SOC 2, HIPAA, GDPR, PCI DSS, EU AI Act, AI risk frameworks) and ability to translate into product requirements.
Experience with consumption-based or outcome-based pricing for AI products.
Multilingual product experience or experience shipping for markets outside North America.

Responsibilities

Define and ship the platform layer that lets an AI agent reason over a goal, call real business systems, respect enterprise guardrails, hand off to a human with full context, and be evaluated with the same rigor a contact center applies to its best people.
Own the agentic platform and agent builder, including agent orchestration, tool use and actions, knowledge grounding and retrieval, guardrails and control, agent lifecycle, and multi-agent patterns.
Own the developer platform, APIs, and ecosystem, including public APIs, SDKs, webhooks, event streams, interoperability with tooling standards, integration and connector strategy, platform quality attributes, and developer experience.
Own evaluation, observability, and model operations, including the evaluation system, production observability, model lifecycle, and unit economics.
Own customer engagement outcomes, including key metrics like containment, resolution rate, FCR, AHT, transfer rate, CSAT, and revenue outcomes, as well as voice-native quality, agent assist, multilingual and omnichannel parity, and pricing.
Write strategy documents, PRDs, and decision records.
Engage with customers through design partner programs and by analyzing operational data.
Prototype agents using RingCentral's tooling.
Make explicit calls about what not to build and defend them with evidence.
Partner with security, legal, privacy, pricing, support, and enablement teams.