Zoom Video Communications

5 days ago

AI Agent Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Design, build, and operationalize autonomous AI agents for enterprise workflows, going beyond chatbot experiences with multi-step reasoning and dynamic tool use. Lead agentic architecture, orchestration, memory/state, runtime services, sandboxing, and lifecycle management. Develop evaluation and observability to track accuracy, reasoning, latency, and cost, and implement safety guardrails with human-in-the-loop fallbacks. Optimize for low-latency, high-throughput reliability and partner with product, data science, and UX teams to deliver AI-native experiences.

Location: Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design robust agentic architectures, multi-agent systems, and orchestration logic, including runtime, memory, state, tool invocation, sandboxing, and lifecycle management.
•Build automated evaluation harnesses and observability pipelines to measure and monitor accuracy, reasoning capability, latency, and operational cost in production.
•Implement operational guardrails, error handling, human-in-the-loop fallback mechanisms, and access controls for safe, predictable, compliant behavior.
•Optimize agent infrastructure for low latency, high throughput, and reliability at scale, partnering with infrastructure teams for resource utilization and cost management.
•Partner with product managers, data scientists, and UX designers to translate workflows into seamless AI-native experiences and shape technical roadmaps.

Pay and Benefits

Salary: USD 177,100 - 387,500 annually

Key Requirements

•Demonstrate expertise in Python, Go, TypeScript, or similar languages, applying software engineering principles to build AI agent systems and multi-agent orchestration frameworks.
•Have expertise in LLM and agent mechanisms, including LLM API, KV Cache, Agent Loop, tool use, reasoning, planning, MCP, memory, subagent, and multi-agent systems.
•Exhibit proficiency in prompt, context, and harness engineering.
•Demonstrate experience with AI coding tools such as Claude Code, Cursor, and Copilot, with strong understanding of LLM-based reasoning and autonomous agent patterns.
•Possess experience with cloud-native AI infrastructure, including Kubernetes, vector databases, and model serving, plus a Bachelor’s in Computer Science/AI/ML/Cognitive Science or equivalent practical experience.

Experience:EnterpriseGenAICloud-native

Education:Bachelor's in Computer Science, AI, ML, Cognitive Science (or equivalent practical experience)

Skills:Problem-solvingCollaborationCommunication

Tech Stack:PythonGoTypeScriptLLM APIKV CacheAgent LoopTool UsePromptContextMCPMemoryMulti-Agent systemsClaude CodeCursorCopilotKubernetesVector databasesModel servingObservabilitySandboxing

Company Brief

Zoom Video Communications

Provides video conferencing, chat, phone, webinar, and collaboration software for businesses, schools, and individuals. Its platform is widely used for remote meetings, virtual events, and hybrid work communication.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 2011

Website LinkedIn

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Zoom Video Communications

5 days ago

AI Agent Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Seattle

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design robust agentic architectures, multi-agent systems, and orchestration logic, including runtime, memory, state, tool invocation, sandboxing, and lifecycle management.
•Build automated evaluation harnesses and observability pipelines to measure and monitor accuracy, reasoning capability, latency, and operational cost in production.
•Implement operational guardrails, error handling, human-in-the-loop fallback mechanisms, and access controls for safe, predictable, compliant behavior.
•Optimize agent infrastructure for low latency, high throughput, and reliability at scale, partnering with infrastructure teams for resource utilization and cost management.
•Partner with product managers, data scientists, and UX designers to translate workflows into seamless AI-native experiences and shape technical roadmaps.

Pay and Benefits

Salary: USD 177,100 - 387,500 annually

Key Requirements

•Demonstrate expertise in Python, Go, TypeScript, or similar languages, applying software engineering principles to build AI agent systems and multi-agent orchestration frameworks.
•Have expertise in LLM and agent mechanisms, including LLM API, KV Cache, Agent Loop, tool use, reasoning, planning, MCP, memory, subagent, and multi-agent systems.
•Exhibit proficiency in prompt, context, and harness engineering.
•Demonstrate experience with AI coding tools such as Claude Code, Cursor, and Copilot, with strong understanding of LLM-based reasoning and autonomous agent patterns.
•Possess experience with cloud-native AI infrastructure, including Kubernetes, vector databases, and model serving, plus a Bachelor’s in Computer Science/AI/ML/Cognitive Science or equivalent practical experience.

Experience:EnterpriseGenAICloud-native

Education:Bachelor's in Computer Science, AI, ML, Cognitive Science (or equivalent practical experience)

Skills:Problem-solvingCollaborationCommunication

Tech Stack:PythonGoTypeScriptLLM APIKV CacheAgent LoopTool UsePromptContextMCPMemoryMulti-Agent systemsClaude CodeCursorCopilotKubernetesVector databasesModel servingObservabilitySandboxing

Company Brief

Zoom Video Communications

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Jose, United States

Founded: 2011

Website LinkedIn