Snowflake

3 months ago

Staff Software Engineer, Cortex AI Infrastructure

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Staff Software Engineer focuses on backend infrastructure for AI/ML products in Cortex AI Infrastructure. You will architect agent runtimes, scale retrieval-augmented generation infra, build evaluators, productionize AI workflows, and optimize performance and cost across multi-tenant microservices. Requires distributed systems expertise, Go/Java, Python, and cloud-native architectures. Join Cortex Apps team building AI for enterprise data at Snowflake.

Location: Menlo Park

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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, including vector database integration, scalable search indexing, query processing, result ranking, semantic caching, and automated metadata extraction.
•Build the Evals Engine: Develop automated infrastructure to run massive-scale golden set simulations, error analysis pipelines, and hillclimbing experiments.
•Productionize AI Workflows: Collaborate with modeling team to turn raw LLM capabilities into hardened, multi-tenant microservices with guardrails and observability.
•Optimize Performance & Cost: Direct infra strategy for model routing, prompt caching, and token optimization to keep Snowflake’s AI features efficient.

Pay and Benefits

Salary: USD 236,000 - 339,250 annually

Key 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.

Experience:5+ yearsAIEnterprise data

Education:Bachelor's

Skills:Problem-solvingCollaborationCommunication

Tech Stack:GoJavaPythonKubernetesFoundationDBVector indicesAI orchestrationDistributed systemsBackend infrastructure

Company Brief

Snowflake

Provides a cloud-native data platform for data warehousing, data engineering, data science, and analytics, enabling organizations to store, process, and share large-scale data across multiple cloud providers with elastic scalability and performance.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn

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Snowflake

3 months ago

Staff Software Engineer, Cortex AI Infrastructure

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Menlo Park

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key 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, including vector database integration, scalable search indexing, query processing, result ranking, semantic caching, and automated metadata extraction.
•Build the Evals Engine: Develop automated infrastructure to run massive-scale golden set simulations, error analysis pipelines, and hillclimbing experiments.
•Productionize AI Workflows: Collaborate with modeling team to turn raw LLM capabilities into hardened, multi-tenant microservices with guardrails and observability.
•Optimize Performance & Cost: Direct infra strategy for model routing, prompt caching, and token optimization to keep Snowflake’s AI features efficient.

Pay and Benefits

Salary: USD 236,000 - 339,250 annually

Key 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.

Experience:5+ yearsAIEnterprise data

Education:Bachelor's

Skills:Problem-solvingCollaborationCommunication

Tech Stack:GoJavaPythonKubernetesFoundationDBVector indicesAI orchestrationDistributed systemsBackend infrastructure

Company Brief

Snowflake

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Bozeman, United States

Founded: 2012

Website LinkedIn