Enterprise AI Product Engineer

RingCentral•Belmont, CA

About The Position

Say hello to opportunities. It’s not everyday that you consider starting a new career. We’re RingCentral, and we’re happy that someone as talented as you is considering this role. First, a little about us, we’re a $2 Billion annual revenue company with double digit Annual Recurring Revenue (ARR) and a $93 Billion market opportunity in UCaaS, Contact Center and AI-powered adjacencies. We invest more than $250 million annually to ensure our AI-enabled technology and platforms meet or exceed the needs of our customers. RingSense AI is our proprietary AI solution. It’s designed to fit the business needs of our customers, orchestrated to be accurate and precise, and built on the same open platform principles we apply to our core software solutions. RingCentral's Enterprise AI organization is looking for a strong hybrid: someone who can walk into a business meeting, identify the enterprise AI opportunity, architect the solution, and then build it. This is not a traditional product management role. We are hiring an AI Product Engineer — a hands-on technologist with enough product instinct to own the “why,” enough architecture depth to define the “how,” and enough engineering skill to actually build it. You will sit within our product management team and serve as a force multiplier — partnering with business stakeholders & product managers to uncover AI opportunities, designing end-to-end solutions, prototyping quickly, and driving production delivery alongside engineering. The emphasis is firmly on building and architecting, with product management as your professional home base.

Requirements

3+ years of hands-on experience building or integrating AI-powered solutions in an enterprise setting (RAG, LLM applications, AI agents, or similar).
Demonstrated ability to architect solutions from scratch — designing data flows, integration patterns, and system components in live stakeholder settings.
Proficiency in at least one scripting or development language (Python strongly preferred; familiarity with JavaScript/TypeScript a plus).
Solid grasp of modern AI/ML concepts: LLMs, embeddings, vector databases, prompt engineering, retrieval-augmented generation, and agent frameworks.
Experience integrating with enterprise APIs and platforms (REST, GraphQL, OAuth 2.0, webhooks) and familiarity with data stores (PostgreSQL, MongoDB, Redis, or similar).
Strong communication skills — able to explain technical architecture clearly to executives, and to translate fuzzy business problems into precise technical requirements.
A track record of shipping: prototypes that became products, pilots that became programs.

Nice To Haves

Exposure to enterprise systems: Salesforce, Workday, NetSuite, ServiceNow, or similar HRIS/CRM/ITSM platforms.
Experience with conversational AI platforms: Google Dialogflow CX, Microsoft Copilot Studio, or equivalent.
Familiarity with cloud AI/ML services on AWS, GCP, or Azure.
Background or coursework in product management, systems design, or solutions architecture.
Comfort with SQL and analytical tooling for evaluating AI system performance.

Responsibilities

Architect AI Solutions End-to-End Join business meetings and workshops to uncover automation and AI opportunities in real time; translate them into concrete solution architectures on the spot. Design and recommend solution patterns — RAG pipelines, agentic workflows, MCP integrations, prompt/eval frameworks — choosing the right approach for each use case. Own build-vs-buy decisions: evaluate third-party AI tools (Copilot, Gemini, Claude, etc.) against custom in-house builds using structured technical and business criteria. Define data flows, integration points, and system contracts across enterprise platforms such as Salesforce, Workday, NetSuite, and cloud AI services (AWS, GCP, Azure).
Build and Ship Hands-On Develop working prototypes, proof-of-concepts, and production-grade AI features — not slide decks. Implement and iterate on RAG pipelines, LLM orchestrations, agentic workflows, API integrations, and chatbot/copilot experiences. Establish telemetry and LLM evaluation frameworks (correctness, faithfulness, latency, cost, token usage) and monitor live systems post-launch. Collaborate closely with engineering teams through code reviews, technical workshops, and paired development sessions.
Drive Product Direction Partner with business units (Sales, Marketing, HR, Finance, Legal, CX) to identify high-impact use cases, quantify ROI, and define measurable success criteria. Maintain the product roadmap for AI initiatives, owning quarterly planning, backlog prioritization, and end-to-end AI-DLC from discovery through launch and iteration. Keep a current AI tool landscape and comparison matrix spanning general-purpose copilots and function-specific enterprise apps. Use agile rituals and rapid experimentation to learn quickly and keep delivery momentum.
Evangelize and Enable Serve as the organization’s resident AI practitioner: educate stakeholders on what’s possible, set realistic expectations, and demystify technical concepts for non-technical audiences. Lead AI training sessions, internal demos, and working sessions to accelerate adoption across business functions. Monitor and communicate the quantifiable impact of launched AI solutions (time saved, quality, adoption, CSAT).

Benefits

Comprehensive medical, dental, vision, disability, life insurance
Health Savings Account (HSA), Flexible Spending Account (FSAs) and Commuter benefits
Voluntary supplemental health coverage and life insurance
401K match and ESPP
Paid time off and paid sick leave
Paid parental and pregnancy leave
Family-forming benefits (IVF, Preservation, Adoption etc.)
Emergency backup care (Child/Adult/Pets)
Employee Assistance Program (EAP) with counseling sessions available 24/7
Free legal services that provide legal advice, document creation and estate planning
Employee bonus referral program
Student loan refinancing assistance
Employee 1:1 coaching, perks and discounts program