Enterprise AI Senior Product Manager - IT at RingCentral

Belmont, California, United States

Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, UCaaS, Contact Center, AIIndustries

2 years of experience in building or integrating AI-powered solutions in enterprise setting, and 5 years in product management
Bachelor’s degree in a technical field (Computer Science, Engineering) or an MBA with a strong passion for technology
Solid grasp of fundamental AI and Machine Learning concepts and the modern AI landscape
Strong analytical and problem-solving skills, with the ability to break down complex problems and propose data-informed, AI-driven solutions
Excellent communication skills, with the ability to effectively collaborate with both technical and non-technical teams
Natural inclination towards leadership and the ability to influence cross-functional teams to get things done
Genuine passion for AI and its potential to transform the employee experience
Bonus: Familiarity with core AI concepts like Retrieval-Augmented Generation (RAG) and Vector Databases
Bonus: Exposure to enterprise systems (Salesforce, Workday) and comfort with SQL
Bonus: Experience with cloud platforms (GCP, AWS, Azure) and their AI/ML services
Bonus: Understanding of APIs, webhooks, and modern authentication mechanisms

Embed with business units (Sales, Marketing, HR, etc.) to map their workflows, quantify their pain points, and translate those opportunities into clear product requirements with measurable success metrics (time saved, quality, adoption)
Act as the in-house expert on the AI landscape, maintaining a comparison matrix of tools (from general-purpose copilots like Gemini and Claude to function-specific apps) and guide teams to the best solution for their needs using a structured evaluation framework
Lead build-vs-buy decisions using a pragmatic, business-first framework to advise when to integrate third-party solutions versus building in-house AI agents, staying on the pulse of the latest AI trends, from Generative AI and RAG to the competitive landscape
Own the roadmap and SDLC: drive the product strategy, quarterly planning, and end-to-end delivery from discovery to launch and iteration, using agile rituals to learn quickly and proactively overcome roadblocks by making smart trade-off decisions
Partner deeply with engineering: work side-by-side with engineers to co-create prototypes and production features (e.g., RAG pipelines, prompts, and integrations with CRMs/ITSMs/HRIS), establishing and monitoring key LLM evaluations for correctness, cost, and latency
Drive adoption: serve as an AI evangelist within the organization, leading training sessions, educating stakeholders, and measuring the quantifiable success of launched features to guide future improvements