Senior/Principal Product Manager

RingCentral•Belmont, CA

1d•Remote

About The Position

RingCentral is seeking a Senior/Principal Product Manager to define and ship the platform layer for an AI agentic platform. This role involves owning the strategy and execution for agent orchestration, tool use, knowledge grounding, guardrails, agent lifecycle, multi-agent patterns, developer platform, APIs, ecosystem, evaluation, observability, model operations, and customer engagement outcomes. The ideal candidate will have a strong track record in product management, particularly in conversational AI, agentic AI, or ML-powered products in production, with experience shipping LLM-based products at scale. This role requires technical fluency, platform product experience, enterprise B2B SaaS depth, and quantitative rigor. The candidate will be responsible for writing strategy documents, PRDs, and decision records, engaging with customers, prototyping, making strategic sequencing calls, and partnering across various teams. RingCentral is a global leader in AI-powered business communications, with a strong focus on AI-first customer engagement and a commitment to diversity and inclusion.

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 (not a pilot or demo).
Technical fluency to be a real counterpart to engineering (reason confidently about prompting and context management, retrieval, tool and function calling, latency and token budgets, fine-tuning versus prompting tradeoffs, and architectural choices).
Platform product experience (owned APIs, SDKs, or extensibility surfaces where users were developers or technical administrators, understanding of versioning and backward compatibility).
Enterprise B2B SaaS depth (navigated security reviews, procurement, admin and permission models, audit requirements).
Quantitative rigor (define success metrics before building, instrument them, change mind based on data, comfortable in SQL or equivalent analytics environment).
Excellent written communication (writing sample will be requested).
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, or enterprise agent builder) where AI agent quality was personal accountability.
Hands-on voice AI experience (real-time streaming, sub-second latency budgets, ASR and TTS selection, operational realities of telephony).
Built or owned an evaluation harness for non-deterministic systems.
Forward-deployed or solutions-adjacent experience (personally stood up an AI agent inside a customer's environment and owned the outcome).
Conversation design background, or credible collaboration with conversation designers.
Contact center domain knowledge (routing, workforce engagement management, quality assurance, VP of Customer Care metrics).
Familiarity with the AI governance landscape (SOC 2, HIPAA, GDPR, PCI DSS, EU AI Act, recognized AI risk frameworks) and ability to turn them into product requirements.
Experience with consumption-based or outcome-based pricing for AI products.
Multilingual product experience, or having shipped 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, integration and connector strategy, platform quality attributes, and developer experience.
Own evaluation, observability, and model operations, including the evaluation system, production observability, model lifecycle, unit economics, and cost-quality-latency tradeoffs.
Own customer engagement outcomes, including key metrics like containment, resolution rate, CSAT, and revenue outcomes, as well as voice-native quality, agent assist, multilingual and omnichannel parity.
Write strategy documents, PRDs, and decision records.
Run design partner programs, sit inside real deployments, and listen to real call recordings.
Prototype agents yourself in our own tooling.
Make explicit calls about what we are not building, and defend them to Sales and to executives.
Partner across security, legal, privacy, pricing, support, and enablement teams.