Forward Deployment Engineer

Zoom is a company focused on building the best collaboration platform for enterprises, and they are seeking a Forward Deployment Engineer to lead the deployment of next generation Zoom Virtual Agents. The role involves designing and deploying conversational AI solutions using large language models (LLMs) and agentic frameworks to enhance customer interactions.

Responsibilities:

• Leading multi-step conversational workflow design using agentic frameworks to enable LLM agents to execute complex multi-tool tasks, including database checks and transactions
• Fine-tune the underlying Large Language Models (LLMs) to ensure optimal performance, low latency, and minimal hallucination in real-time voice conversations
• Developing and deploy custom full-stack Python/JS to connect the agent's decision-making with customer back-end systems (CRM, ERP, knowledge bases) as external "tools."
• Crafting and iterating advanced LLM prompts (e.g., chain-of-thought, few-shot) to guide conversation, maintain context, and ensure accurate tool use in live voice interactions
• Prompt-engineer TTS components (e.g., ElevenLabs, Azure, Cartesia) to fine-tune tone, pacing, emphasis, and prosody to context and brand
• Conducting A/B testing and performance monitoring on TTS output, ensuring high acoustic quality, latency requirements, and emotional appropriateness
• Acting as the embedded technical expert, working directly with customer engineering and executive teams to map complex business goals to agentic solutions
• Managing end-to-end production deployments with continuous optimization and performance tuning driven by real-world voice traffic data
• Translating field challenges, LLM failure modes, and TTS needs into actionable input for Core Engineering and Product to drive platform innovation

Requirements:

• Have 3+ years in a technical, customer-facing role (FDE, Solutions Architect, Technical Lead) focused on AI/ML or highly technical SaaS products
• Possess proven hands-on experience designing and deploying LLM solutions using modern agentic frameworks (e.g., LangChain, LlamaIndex, internal tools)
• Have deep expertise in voice stacks and TTS integration, using prompt engineering to control prosody, tone, and pacing
• Possess proven ability to write and manage iterative prompts guiding both generative text logic and speech synthesis quality (prosody and emotion)
• Have solid software development skills in Python for prototyping, API integration, and production deployment, coupled with familiarity with modern DevOps practices
• Own exceptional ability to distill complex AI and engineering concepts into clear, actionable insights for both technical teams and C-level executives