Staff Software Engineer

ZoomSan Jose, CA
Hybrid

About The Position

Zoom is looking for an innovative and skilled Staff Software Engineer to join our Zoom Virtual Agent (ZVA) team. The focus will be on improving the quality, reliability, and performance of Zoom's AI-powered virtual agent - an intelligent system that autonomously resolves customer inquiries before escalating to a human agent. The Zoom Virtual Agent team is committed to transforming customer experience through AI-driven automation. We are passionate about building intelligent, production-grade systems that handle real customer interactions at scale - reducing the need for human escalation and delivering faster, more accurate resolutions. We operate with a startup mentality: fast-moving, high-ownership, and focused on building foundational technology that will define the future of AI-powered customer service.

Requirements

  • Have an advance degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.
  • 10+ years of software engineering experience with rich system architecture knowledge & skills.
  • With at least 3–5 years working directly on AI-powered products, LLM-based systems, or conversational AI agents in production.
  • Have track record of diagnosing and improving AI agent quality — with specific examples of identifying failure modes and driving measurable improvements.
  • Have prompt engineering skills, including system prompt design, context management, and prompt chain optimization.
  • Have engineering scope — experience leading technical direction for a product area or team, with the ability to both design systems and execute on them.
  • Have experience deploying and operating LLM-based systems in production at scale — not just research or prototyping.

Nice To Haves

  • Having DSPy/APO/GEPA experience is a plus.
  • Have experience with ML or model training is a plus — candidates who have transitioned from MLE into SWE roles are strongly welcomed.

Responsibilities

  • Diagnosing and resolving AI agent quality issues — identifying whether failures stem from model behavior, prompt design, or system architecture, and driving the fix end-to-end.
  • Designing and optimizing system prompt architectures, few-shot examples, and prompt chains to improve agent reliability, accuracy, and resolution rates.
  • Building and maintaining evaluation pipelines to continuously measure agent quality, detect regressions, and validate improvements before production deployment.
  • Architecting scalable, maintainable systems that support high-performance AI agent operation at scale.
  • Collaborating with product managers, model teams, and engineering leadership across US and China time zones to align on quality goals and delivery timelines.
  • Setting the technical direction for agent quality on the team — mentor engineers, influence the roadmap, and drive measurable improvements in customer-facing outcomes.

Benefits

  • As part of our award-winning workplace culture and commitment to delivering happiness, our benefits program offers a variety of perks, benefits, and options to help employees maintain their physical, mental, emotional, and financial health; support work-life balance; and contribute to their community in meaningful ways.
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