AI Software Engineer - Search Infrastructure

AI Software Engineer – Search Infrastructure

What you can expect:
We're building the next-generation AI‑native knowledge platform to help organizations easily access and retrieve internal knowledge using the power of LLMs. You’ll join a fast‑moving engineering team to build scalable, secure, and intelligent Retrieval‑Augmented Generation (RAG) infrastructure—powering enterprise search, AI assistants, and knowledge discovery experiences.

About the Team:
You’ll collaborate with world‑class engineers, designers, and product thinkers to define what “AI‑powered search” really means in the enterprise. As a core engineer on this team, you'll work across real‑time document pipelines, vector databases, and permission‑aware retrieval to push the boundaries of applied LLM systems at scale.

• Design and implement a scalable RAG system for real‑time Q&A across internal content (meetings, messages, documents, whiteboards, videos, etc.).
• Build robust ingestion and indexing pipelines for semi‑structured data sources with fine‑grained, permission‑aware access control.
• Develop APIs and backend systems to enable efficient querying, retrieval, and ranking.
• Collaborate with ML/NLP engineers to iterate on embedding models and improve search quality.
• Ensure reliability, low latency, and scalability across the entire data retrieval and augmentation stack.
• Monitor system performance and optimize for high‑throughput, low‑latency workloads under real‑world load.

• Bachelor's degree and 4+ years of experience in backend or distributed systems engineering.
• Productivity mindset with experience using AI tools effectively.
• Experience designing and operating large‑scale data ingestion pipelines (message queues, vector stores, Temporal, Elasticsearch, etc.).
• Track record of building highly available, multi‑tenant backend services.
• Experience with document‑level permission modeling and secure data handling.
• Proficiency with cloud‑native tools such as Docker, Kubernetes, and AWS.
• Experience in Go is a bonus.
• Experience integrating with SaaS platforms (Google Workspace, Microsoft 365, Slack, etc.).

Salary Range or On Target Earnings:
Minimum $ – Maximum $. In addition to the base salary and/or OTE listed, Zoom has a Total Direct Compensation philosophy that takes into consideration base salary, bonus, and equity value. Starting pay will be based on a number of factors and commensurate with qualifications & experience. We also have a location‑based compensation structure; there may be a different range for candidates in this and other locations.

Benefits:
Our benefits program offers a variety of perks, benefits, and options to help employees maintain physical, mental, emotional, and financial health; support work‑life balance; and contribute to the community in meaningful ways. Learn more at (Use the "Apply for this Job" box below)..

At Zoom, we believe great work happens when people feel supported and empowered. We’re committed to fair hiring practices that ensure every candidate is evaluated based on skills, experience, and potential. If you require an accommodation during the hiring process, let us know—we’re here to support you at every step.

We welcome people of different backgrounds, experiences, abilities and perspectives, including qualified applicants with arrest and conviction records and any qualified applicants requiring reasonable accommodations in accordance with the law. If you need assistance navigating the interview process due to a medical disability, please submit an Accommodations Request Form at  This form is solely for applicants who require an accommodation due to a qualifying medical disability.

Non‑accommodation‑related requests, such as application follow‑ups or technical issues, will not be addressed.

Zoom is proud to be an equal‑opportunity workplace and an affirmative action employer. All your information will be kept confidential according to EEO guidelines.