About the role
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.
About
The Role You will play a lead role in a high-impact transformation: evolving RingCentral’s 1,300-person global technical support organization from a human-centric operation into a hybrid, agentic AI ecosystem. We are moving beyond traditional chatbots to build autonomous, goal-driven multi-agent systems capable of reasoning, planning, and executing complex technical support workflows to resolve customer issues at scale. As a Senior Agentic AI Engineer, you will be at the forefront of this revolution. You will architect, develop, and deploy intelligent agents that understand nuanced customer problems, interact with internal systems, and autonomously drive resolutions. This is a unique opportunity to shape the future of enterprise customer support at a leading global communications company. Key
Responsibilities Architect and Build Agentic Systems: Design and implement autonomous, LLM-powered agents for complex support workflows. Develop Core AI Capabilities: Build robust retrieval-augmented generation (RAG) pipelines and tool-use capabilities to give agents access to internal data, diagnostic and resolution tools, and knowledge bases. System Integration: Seamlessly integrate AI agents with RingCentral’s proprietary infrastructure, APIs, and other enterprise systems using the model context protocol (MCP). Optimize Performance & Reliability: Ensure high accuracy, low latency, and enterprise-grade reliability. Implement robust agentic observability, evaluation, and guardrails to prevent hallucination and execution loops. Lead & Collaborate: Serve as a technical lead and individual contributor (IC), setting best practices for prompt engineering, model evaluation, and agent architecture. Collaborate cross-functionally with Support, Product, and Engineering teams. Continuous Innovation: Stay at the bleeding edge of AI research. Evaluate new foundation models, agentic frameworks, and optimization techniques.