The Cortex team is building the future of AI for enterprise data. This role focuses on the
Search infrastructure that powers our flagship products like CoWork, Cortex Code & Cortex Agentsfast, reliable, scalable and secure at the enterprise level.
You will be building high-performance retrieval engines (leveraging vector search, hybrid search, and semantic indexing) that power Snowflake Cortex. This involves optimizing how billions of rows of data areindexed and retrieved in milliseconds.
What you will do in this role:- Architect Agentic Runtimes: Build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management.
- Scale Context Engineering Infra: Design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable and efficient search indexing, query processing, and result ranking, semantic caching, and automated metadata extraction.
- Build the 4Evals Engine4: Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and 4hillclimbing4 experiments.
- Productionize AI Workflows: Collaborate with the modeling team to take raw LLM capabilities and turn them into hardened, multi-tenant microservices with strict guardrails and observability.
- Optimize Performance & Cost: Direct the infra strategy for model routing, prompt caching, and token optimization to ensure Snowflake9s AI features are the most efficient in the industry.
Requirements:- Education: Bachelor9s degree in Computer Science or a related technical field.
- Experience: 9 + years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products.
- Technical Stack: Deep proficiency in Go or Java (for systems) and Python (for AI orchestration).
- Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (Kubernetes, FoundationDB, etc.).
- Domain Expertise: Familiarity with the 4plumbing4 of AI: vector indices, agent platforms, and building scalable data pipelines.
(Bonus) Experience with:- Query optimization and SQL engine internals.
- Designing multi-tenant systems that handle sensitive enterprise data at scale.
- Developing search infrastructure for large-scale applications.
- Direct experience with any of the subsystems outlined above.
Every Snowflake employee is expected to follow the company9s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company9s data security plan as an essential part of their duties. It is every employee9s duty to keep customer information secure and confidential.
Snowflake is growing fast, and we9re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.
How do you want to make your impact?
For jobs located in the United States, please visit the job posting on the Snowflake Careers Site for salary and benefits information: careers.snowflake.com
