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Snowflake

Senior Software Engineer - Cortex AI - FDE

RemoteUnited States only
Published
Role
AI / ML
Experience
Senior
Employment
Full-time
Salary not disclosedModel estimate · $165k–$205k/yrMedium confidence · 80 comparable rolesMedian $185k · Based on same company, role, seniority, location, requirements, company profile, employment type, and work arrangement
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Open to US only. Set where you work from to check your eligibility.

Core skills

Go/JavaPython

Required skills

KubernetesFoundationDB

Optional skills

SQL

What you'll do

  • 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.

What they require

  • Education: Bachelor’s degree in Computer Science or a related technical field.
  • Experience: 7+ years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products.
  • 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 in a customer-facing technical role — you have explained a hard failure to a frustrated external audience and been believed, you can produce both the internal analysis and the customer-safe version.

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🇺🇸 United StatesData & AnalyticsEnterprise

What people say about this company

3.7/ 5

Salary not disclosed