Jobs at Zoom

Own and drive enterprise infrastructure product portfolio covering data sovereignty, network resilience, and cryptographic key management. Define strategy and roadmap, influence cross-functional teams, engage enterprise customers, and lead launches and adoption while measuring business outcomes.

Conduct applied large language model research for Zoom AI Companion features, focusing on post-training, reinforcement learning, reward modeling, evaluation, agentic AI, tool usage, multimodal understanding, long-context modeling, and retrieval-augmented generation. Build training and evaluation pipelines, benchmarks, and annotation workflows while collaborating with scientists, engineers, and product managers to translate research into production-ready solutions.

Build and deploy end-to-end production ML models to predict customer expansion and churn. Design automated retraining, monitoring, and incident response pipelines. Partner with engineering, product, and GTM teams on telemetry and data contracts. Run experiments, deliver analyses, and communicate findings to senior leadership to inform revenue strategy.

Design, deploy, and validate production LLM-based voice agents for customers, integrating with CRMs and telephony. Tune ASR/TTS and conversational turn-taking, build evaluation frameworks, capture product gaps, and transition successful pilots to Professional Services with documentation and playbooks.

Contribute to AI research in LLM post-training and reinforcement learning, developing scalable systems for Zoom's AI Companion. Engage in innovative research, implement model architectures, and partner with teams to translate prototypes into production systems.

Develop and optimize AI runtimes for large language models and other AI services, focusing on performance, cost efficiency, and scalability.

The AI Engineer will design scalable APIs and SDKs for AI services, collaborate with AI research teams, and ensure API security and performance. Responsibilities include building processing systems, integrating services, and maintaining documentation.

Design and build scalable, permission-aware retrieval and reasoning systems for Zoom's AI Companion. Implement vector and hybrid search, RAG pipelines, ranking and evaluation frameworks, indexing, and NLP/entity-extraction pipelines. Collaborate with product, infrastructure, and research teams to deploy production-grade, multi-tenant search and LLM-based applications.

Design, build, and maintain AI-embedded web applications and backend microservices. Implement end-to-end model lifecycle, data pipelines, CI/CD, observability, automated tests, and technical documentation while collaborating with product, research, and platform teams.

The Software Engineer will design and implement customer-facing software, focusing on security and cloud solutions, while collaborating with cross-functional teams.

Design, build, and operate ZoomMates agent harness and framework: orchestration, tool integration, memory, multi-step reasoning, SDK/API surfaces, evaluation and benchmarks, and production-grade services embedded into Zoom products.

Lead development of Zoom chat and meeting frontend modules using React/Vue and Zoom SDK, implement hybrid WebView bridges, handle streaming via WebSocket/Zoom realtime APIs, ensure WCAG 2.1 accessibility, build CI/CD pipelines, optimize performance under concurrency, and coordinate a distributed multilingual engineering team.

Lead and architect scalable agentic AI runtime services integrating LLM-based reasoning. Manage and mentor a distributed team, drive technical roadmap, deploy models in microservice environments, and collaborate cross-functionally to deliver production conversational AI solutions.

Design and optimize GenAI solutions, collaborate with teams, enhance system performance, present technical findings, and stay updated on GenAI advancements.

The AI Infrastructure Engineer will develop and optimize infrastructure for training large language models, focusing on distributed systems and GPU programming.

Design and implement backend orchestration for agent workflows and runtime in microservices. Build scalable LLM-powered systems (RAG, tool-use, multi-step reasoning), integrate LLM/TTS/ASR, develop agents with frameworks like LangChain/Dify/OpenAI SDK, optimize prompts, run integration tests, and collaborate with research and product teams to deploy agentic AI across verticals.

Design, deploy, and maintain large-scale ML workflows and knowledge graph services. Build production-ready LLM and RAG-based search pipelines, data ingestion/preprocessing, feature stores, monitoring, and security. Collaborate with cross-functional teams, document systems, research advanced ML/NLP techniques, optimize knowledge graph algorithms, and mentor junior engineers.

Manage end-to-end global VAT and indirect tax compliance across multiple jurisdictions, support month-end/quarter-end indirect tax accounting, assist with e-invoicing and digital tax reporting, collaborate on tax technology automation and AI-driven improvements, respond to audits, and provide tax advisory to internal and customer-facing teams.

Lead operational strategy for partner marketing programs, building scalable processes, AI-driven automation, and reporting to drive partner-sourced revenue. Manage MDF/payment workflows, budget operations, partner data models, dashboards, and cross-functional execution with Marketing, IT, Finance, Legal, and leadership.

Lead the vision and roadmap for AI-agent orchestration across revenue workflows. Partner with Engineering, AI/ML, Design, customers, and go-to-market teams to build reliable, intuitive, human-controllable products. Own the product lifecycle from customer insight and prototyping through launch, adoption, packaging, and commercialization. Shape how agents, context, data, tools, and workflows combine to deliver differentiated enterprise revenue solutions.