---
title: 'Staff Software Engineer, Cortex AI Search Infrastructure at Snowflake'
canonical: 'https://feeny.ai/job/staff-software-engineer-cortex-ai-search-infrastructure-snowflake-menlo-park-j5d8xyax30bc'
type: 'job'
last_seen: '2026-11-06'
---

# Staff Software Engineer, Cortex AI Search Infrastructure at Snowflake

- **Company:** [Snowflake](https://feeny.ai/companies/snowflake)
- **Location:** Menlo Park, CA
- **Compensation:** $236k–$339k
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-09-17
- **Last confirmed live:** 2026-11-06
- **Apply:** https://jobs.ashbyhq.com/snowflake/a1f1779b-464c-48f6-a664-56314825c8ac/application

**Skills:** Go, Java, Python, Distributed systems, Backend infrastructure, AI/ML product infrastructure, Database internals, Cloud-native architecture, Kubernetes, FoundationDB, Vector indices, Agent platforms, Scalable data pipelines, Query optimization, SQL engine internals, Multi-tenant system design, Search infrastructure design

> Build and scale backend infrastructure for AI-native enterprise products, focusing on agentic AI workflows, RAG systems, and high-throughput context retrieval. The role involves architecting orchestration engines, optimizing performance and cost, and productionizing LLM capabilities into secure, multi-tenant microse...

## Job description

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. 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 Agents fast, 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 are indexed 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 "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: 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 "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.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee’s duty to keep customer information secure and confidential. Snowflake is growing fast, and we’re 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](http://careers.snowflake.com)

## About Snowflake

## Company Overview
- **One-liner**: Snowflake provides an AI Data Cloud platform that enables enterprises to store, analyze, and securely share their data across multiple clouds and geographies.
- **Entity Type**: Public (NYSE: SNOW)
- **Headquarters**: Bozeman, Montana, United States
- **Founded**: 2012
- **Founders**: Not explicitly listed in the provided search results (widely known co-founders include Benoit Dageville, Thierry Cruanes, Marcin Zukowski – not verified in these search results)

## Core Business
- **Primary Industry**: Enterprise software, cloud data platform
- **Target Customers**: B2B, including large enterprises (e.g., hundreds of the world’s largest companies), mid-market, and SMBs
- **Mission**: “To Mobilize the World’s Data” (Glassdoor) and “empower every enterprise to achieve its full potential through data and AI” (Snowflake Careers page)

## Products & Services
- **Snowflake AI Data Cloud**: A unified, multi-cloud platform that combines data warehousing, data lakes, data sharing, and AI/ML capabilities. Customers can discover, share, and analyze data while running analytic workloads across public clouds (AWS, Azure, GCP).
- **Snowflake Marketplace**: A marketplace for discovering and accessing third‑party data sets and applications.
- **Snowflake‑Powered Applications**: Platform for building and deploying data‑intensive applications.

## Market Standing
- **Valuation/Market Cap**: Not directly provided in search results (as a public company, market cap fluctuates and is available on financial websites).
- **Key Metric**: Annual Revenue – $1 to $5 billion (USD) per Glassdoor.
- **Notable Investors/Partners**: Not explicitly mentioned in the search results (historically backed by Sequoia Capital, Dragoneer, etc. – not verified here).
- **Growth Signals**:
  - Named #1 on the 2023 Fortune Future 50 List ([Fortune.com](https://fortune.com))
  - Listed as a U.S. Best Large Place to Work by BuiltIn in 2024
  - Recognized as one of the “20 Coolest Cloud Software Companies” by CRN in 2022 and 2024
  - Headcount of 5,001–10,000 employees with 30 global locations; actively hiring
  - Revenue range $1B–$5B indicates strong scale

## Competitive Advantages
- **Multi‑Cloud Flexibility**: Operates across AWS, Azure, and GCP, avoiding vendor lock‑in.
- **Unified Data Experience**: One platform for data sharing, analytics, and AI, reducing silos.
- **Separation of Compute and Storage**: Allows independent scaling and cost efficiency (not detailed in provided sources, but a known differentiator).
- **Strong Ecosystem**: Data marketplace and extensive partner network.

## Strategic Focus
- **AI & Data Innovation**: The company’s current emphasis is on making “enterprise AI easy, efficient, and trusted” and integrating AI capabilities into the Data Cloud.
- **Global Expansion**: Active hiring across 30 locations indicates continued geographic growth.
- **Customer‑Centric Development**: Focus on empowering enterprises to achieve “full potential through data and AI.”

## Why Work Here
- **Culture**: Described as “driven by innovation, low egos, high bars, and collaboration” (Snowflake Careers page). Glassdoor rating of 3.9/5 overall (78% approve CEO).
- **Work‑Life Balance**: Glassdoor rates Work/Life Balance at 3.7/5; many remote and hybrid roles available (see Indeed listings).
- **Benefits**: “Benefits & Beyond” program includes competitive compensation, equity, career advancement programs, and commitment to pay equality and veteran hiring.
- **Engineering Focus**: Hiring process includes 2–4 week timeline with technical interviews; the company values impactful, project‑based work for all roles, including interns.
- **Recognition**: Named a Best Large Place to Work (BuiltIn 2024) and future‑focused by Fortune, signaling strong employer brand.

## Sources
1. [Snowflake Careers Overview](https://careers.snowflake.com/us/en)
2. [Life at Snowflake](https://careers.snowflake.com/us/en/snowflake-life)
3. [Snowflake on Glassdoor](https://www.glassdoor.com/Overview/Working-at-Snowflake-EI_IE928471.11,20.htm)
4. [Snowflake Hiring Process](https://careers.snowflake.com/us/en/gethired)
5. [Snowflake on Indeed](https://www.indeed.com/cmp/Snowflake-7f4a7fba)
6. [Snowflake Careers Portal (Ashby)](https://jobs.ashbyhq.com/snowflake) – provided by user

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