Jobs / Zoo***
AI Software Engineer - Search Infrastructure
Zoo*** · Seattle, WA, United States
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Seattle, WA, United States151,800-332,200 USD/yearlyHybrid
Remuneration
151,800-332,200 USD/yearly
Location
Seattle, WA, United States
Visa sponsorship
Sponsors visa
Job summary
- Seattle, Washington, United States - Full time 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.
Benefits
As part of our award-winning workplace culture and commitment to delivering happProgram offers a variety ofAbout UsZoomies help people stay connected so they can get more done together.We’re problem-solvers, working at a fast pace to design solutions with our custoFind room to grow with opportunities to stretch your
Qualifications
- 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.
- 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.
Responsibilities
- 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.
- Designing and implementing a scalable RAG system for real-time Q&A across internal content (meetings, messages, documents, whiteboards, videos, etc.).
- Building robust ingestion and indexing pipelines for semi-structured data sources with fine-grained, permission-aware access control.
- Developing APIs and backend systems to enable efficient querying, retrieval, and ranking.
- Collaborating with ML/NLP engineers to iterate on embedding models and improve search quality.
- Ensuring reliability, low latency, and scalability across the entire data retrieval and augmentation stack.
- Monitoring system performance and optimize for high-throughput, low-latency workloads under real-world load.
- What we’re looking for
- Have a Bachelor's degree and 4+ years of experience in backend or distributed systems engineering
- Have a productivity mindset with experience using AI
Degrees
AssociateBachelorDegree
Industry
EnergySaas
Company size
Enterprise