AI Deployment Strategist

Zoom

1d•$124,000 - $271,200•Remote

About The Position

As an AI Deployment Strategist at Zoom, you will lead the deployment of next-generation Virtual Agents powered by LLMs and agentic frameworks. You will partner directly with strategic customers to translate business goals into automated voice and chat experiences, bridging platform innovation with live production deployments. The Zoom Virtual Agent team develops conversational AI solutions, metrics, intelligence, and evaluation systems to help resolve customer issues efficiently. This role works with advanced LLMs and applied data science to support Zoom’s AI product strategy and deliver customer impact.

Requirements

At least 3 years in a technical, customer-facing role such as Field Deployment Engineer, Solutions Architect, or Technical Lead, focused on AI/ML or highly technical SaaS products.
Hands-on experience designing and deploying LLM solutions using modern agentic frameworks such as LangChain, LlamaIndex, or similar tools.
Deep expertise in voice stacks and TTS integration, including using prompt engineering to control prosody, tone, and pacing.
Ability to write and manage iterative prompts that guide generative text logic and speech synthesis quality, including prosody and emotional nuance.
Software development skills in Python for prototyping, API integration, and production deployment, with familiarity with modern DevOps practices.
Ability to explain complex AI and engineering concepts clearly and provide actionable insights to technical teams and executive stakeholders.

Responsibilities

Design and implement multi-step conversational workflows using agentic frameworks, enabling LLM agents to perform complex multi-tool tasks such as database checks and transactions.
Fine-tune LLMs for performance, low latency, and reduced hallucination in real-time voice conversations.
Build and deploy full-stack Python and JavaScript solutions connecting agent decision-making to customer back-end systems, including CRM, ERP, and knowledge bases.
Create and iterate advanced LLM prompts, including chain-of-thought and few-shot techniques, to guide conversations, maintain context, and support accurate tool use in live voice interactions.
Engineer TTS components, including ElevenLabs, Azure, and Cartesia, to tune tone, pacing, emphasis, and prosody to conversation context and brand standards.
Conduct A/B testing and performance monitoring of TTS output for acoustic quality, latency, and emotional appropriateness.
Partner with customer engineering and executive teams as an embedded technical expert, mapping business goals to agentic AI solutions.
Own end-to-end production deployments and continuously optimize performance based on real-world voice traffic data.
Translate field challenges, LLM failure modes, and TTS requirements into actionable input for Core Engineering and Product.