Immigration sponsorship is not available for this position
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.

Responsibilities:

• 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 ne-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.

What we're looking for:

Requires a Master's degree in Computer Science, a related field, or a foreign equivalent. Must have 2 years of experience in job offered or related occupation. Must have 2 years of experience in the following:

• 2 years of experience with Backend or distributed systems engineering;
• 2 years of experience Building systems with Cassandra, ScyllaDB, Postgres, ElasticSearch, Redis, Kafka, and RabbitMQ;
• 2 years of experience with Cloud-native tools including Docker, Kubernetes, and AWS; and
• 2 years of experience Building highly available, multi-tenant backend services.
• Telecommuting work arrangement permitted: Position may work in various unanticipated locations throughout the U.S. Position does not require domestic or international travel.

Salary Range or On Target Earnings:

Minimum:
$200,000.00

Maximum:
$275,400.00

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.

Note: 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.

Ways of Working
Our structured hybrid approach is centered around our offices and remote work environments. The work style of each role, Hybrid, Remote, or In-Person is indicated in the job description/posting.

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. Click Learn for more information.