# Staff Softare Engineer, Cortex AI Infrastructure

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** Menlo Park, CA
**Role:** Backend Engineering
**Salary:** $236k – $339k/yr
**Experience:** 5+ years
**Skills:** Go, Java, Python, Kubernetes, Foundationdb, RAG, Vector Databases, Distributed Systems, LLMs, Multi-Tenant Systems
**Posted:** 2026-04-27

> Builds scalable backend infrastructure for Snowflake's Cortex AI products, including agentic runtimes, RAG systems, evals engines, and productionized AI workflows. Requires 5+ years in distributed systems and proficiency in Go/Java/Python.

## Job Description

## Responsibilities
- 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 \"Evals Engine\": Develop the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and \"hillclimbing\" 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 Snowflake’s AI features are the most efficient in the industry.

## Requirements
- **Education**: Bachelor’s degree in Computer Science or a related technical field.
- **Experience**: 5+ 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 \"plumbing\" 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.

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