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Senior Software Engineer (Cortex AI, FDE)

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Onsite

Senior Software Engineer (Cortex AI, FDE)

Snowflake

Senior Software Engineer (Cortex AI, FDE)

Skills

SQL QueriesPythonGolangJavaMicroservicesMachine LearningAIKubernetes

2 months ago

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Important information


Contract type:

Permanent

Salary:

$200,000 – $270,000 / year

Location:

Menlo Park, CA, USA

Work mode:

Onsite

Published on:

19 August 2026

What they need


  • The Cortex Apps team is building the future of AI for enterprise data. This role focuses on the backend infrastructure that powers our flagship products like Snowflake Intelligence, Cortex Agents and Search making agentic AI fast, reliable, scalable and secure at the enterprise level
  • You won’t just be using AI tools; you will be building the high-performance systems that orchestrate them. You’ll own and influence the architecture for agent execution environments, high-throughput context retrieval, or the ecosystem that allows our customers to iterate and launch agents in production
  • 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

Benefits

  • Comprehensive health insurance plans
  • Health savings accounts
  • Robust retirement plans
  • Life and disability insurance
  • Weekly online lunch and learns
  • Virtual workout classes
  • Ergonomic work-from-home equipment
  • On-demand mental health and wellness programs
  • Fertility benefits and family planning resources
  • Generous time-off and various leave plans
  • Onsite and Remote Work
  • Employee discounts and pre-tax selections
  • New hire equity + Employee Stock Purchase Plan (ESPP)
  • Quarterly bonus or commission program- Comfort with ambiguity on open-ended, externally-driven problems
  • Technical Stack: Deep proficiency in Go or Java (for systems) and Python (for AI orchestration)
  • Product instinct — you can judge whether one customer’s problem is bespoke or a platform gap worth fixing for everyone. This is the core judgment call
  • Domain Expertise: Familiarity with the “plumbing” of AI: vector indices, agent platforms, and building scalable data pipelines
  • Education: Bachelor’s degree in Computer Science or a related technical field
  • 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
  • Cross-layer debugging — tracing a request across services and root-causing in unfamiliar code from logs and telemetry, not guesswork
  • Experience: 7+ years of experience building distributed systems, high-throughput APIs, or backend infrastructure for AI/ML products
  • Eval frameworks for LLM/agent systems — defining quality metrics and using evals to improve quality systematically over time
  • Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (Kubernetes, FoundationDB, etc.)
  • Query optimization and SQL engine internals
  • Experience with:
  • 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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