RingCentral
AIProductEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“AI Product Engineer at RingCentral. Skills: AI Product Engineering, Solution Architecture, AI Development. Architect AI solutions end-to-end. Join business meetings”
What You'll Achieve.
Drive production delivery; Accelerate adoption; Monitor quantifiable impact
Industry & Context.
Identify AI opportunities; Architect solutions; Build AI solutions
What They're Looking For.
Must Have
3+ years experience building AI solutions, Architect solutions from scratch, Proficiency in Python, Solid grasp of AI/ML concepts, Experience integrating enterprise APIs, Strong communication skills, Track record of shipping prototypes
Nice to Have
Exposure to enterprise systems, Experience with conversational AI platforms, Familiarity with cloud AI/ML services, Background in product management, Comfort with SQL
What You'll Do.
Architect AI solutions end-to-end
Join business meetings
Uncover automation opportunities
Design solution patterns
Recommend solution patterns
Evaluate third-party AI tools
Define integration points
Define system contracts
Develop working prototypes
Build proof-of-concepts
Develop production-grade AI features
Implement RAG pipelines
Iterate on RAG pipelines
Implement LLM orchestrations
Iterate on LLM orchestrations
Implement agentic workflows
Iterate on agentic workflows
Implement API integrations
Iterate on API integrations
Implement chatbot experiences
Iterate on chatbot experiences
Implement copilot experiences
Iterate on copilot experiences
Establish telemetry frameworks
Establish LLM evaluation frameworks
Partner with business units
Identify high-impact use cases
Define success criteria
Maintain product roadmap
Own quarterly planning
Keep AI tool landscape
Use rapid experimentation
Set realistic expectations
Demystify technical concepts
Lead AI training sessions
Conduct internal demos
Lead working sessions
How You'll Work.
Team & Collaboration
Business stakeholders; Product managers; Engineering teams; Business units; Cross-functional teams
Communication Scope
Explain technical architecture; Translate business problems
Process & Methodology
Roadmap planning, Quarterly planning, Backlog prioritization, Agile rituals, Rapid experimentation
Full Job Description
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. **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:
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