Applied AI Engineer
What you can expect
Deploy production AI agents for strategic customers during the sales cycle — taking Zoom Virtual Agent from proof-of-concept to live, trusted daily use within 90 days. Partner across Sales, Product, and Engineering to prove technical value, working hands-on with voice AI, integrations, and real customer data. Turn field insights into platform capabilities that scale, ensuring every deployment makes the next one faster. Your work directly accelerates revenue and shapes the product roadmap.
About the Team
We deploy Zoom Virtual Agent into live customer environments. Our team bridges Sales and Engineering through hands-on technical validation. We exist to convert pilots into production systems. Responsibilities
- Designing and deploying production-ready AI agents during proof-of-concept engagements, integrating with customer CRMs, telephony systems, and knowledge bases using Python and TypeScript
- Engineering voice experiences by tuning speech synthesis, turn-taking, and barge-in across providers to match customer requirements and call profiles
- Building evaluation frameworks with scripted tasks and adversarial scenarios that measure resolution rate, containment, and customer satisfaction as deployment gates
- Capturing product gaps and contributing structured feedback to Engineering, generalising field solutions into reusable platform capabilities
- Transitioning successful pilots to Professional Services or partners with clear documentation, playbooks, and recommendations for ongoing operation
What we’re looking for
- Demonstrate 4+ years in customer-facing technical roles shipping complex SaaS or AI/ML solutions (Solutions Engineering, Technical Account Management, or similar)
- Deploy LLM-based agents with tool use, multi-step orchestration, and guardrails into production customer environments
- Apply voice stack expertise across ASR, TTS, turn-taking, and barge-in, including tuning at least one major provider (ElevenLabs, Azure, Cartesia, or similar)
- Build production integrations in Python with working knowledge of TypeScript or Go, connecting enterprise systems such as CRMs and telephony platforms
- Write tests, log failures, and iterate against measurable targets to validate agent performance before go-live
- Communicate technical concepts to business and engineering stakeholders with clarity and confidence
- Bring contact centre domain knowledge (Genesys, Five9, NICE, Zoom Contact Center) or experience with AI agent platforms (Decagon, Sierra, or similar)
- Contribute to voice agent benchmarks, open-source projects, or have experience deploying in regulated industries (healthcare, financial services, telecom)
Ways of Working Our structured hybrid approach is centered around our offices and remote wo