# Software Engineer, Cortex AI Infrastructure

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** Menlo Park, CA
**Role:** ML Engineering
**Salary:** $160k – $225k/yr
**Experience:** 4+ years
**Skills:** Python, Go, Java, Kubernetes, Foundationdb, RAG, Vector Databases, PyTorch, TensorFlow, Xgboost
**Posted:** 2026-05-21

> Build and scale backend infrastructure powering agentic AI products including orchestration engines, RAG systems, evals infrastructure, and production AI workflows. Requires 4+ years distributed systems experience and deep Python plus Go/Java proficiency.

## Job Description

## What you will do in this role

- Build Agentic Runtimes: Help build and scale the orchestration engines that execute complex agentic workflows, ensuring low-latency tool execution and robust state management.
- Scale Context Engineering Infra: Develop and design high-performance systems for RAG (Retrieval-Augmented Generation), including vector database integration, scalable search indexing, query processing, and semantic caching.
- Develop the "Evals Engine": Build the automated infrastructure required to run massive-scale golden set simulations, error analysis pipelines, and 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: Implement system optimizations for model routing, prompt caching, and token optimization to ensure maximum efficiency.

## Requirements

- Education: Bachelor's degree in Computer Science or a related technical field; Masters or PhD preferred.
- Experience: 4+ years of industry experience designing, building, and supporting distributed systems, high-throughput APIs, machine learning platforms, or data-intensive systems.
- Technical Stack: Deep proficiency in Python (for AI orchestration) and strong experience with Go or Java (for systems). Familiarity with C++ is a plus.
- Systems Thinking: Strong understanding of database internals, distributed state management, and cloud-native architecture (e.g., Kubernetes, FoundationDB). Experience setting up and maintaining CI/CD pipelines is a plus.
- Domain Expertise: Familiarity with the "plumbing" of AI, such as vector indices, agent platforms, building scalable data pipelines, and working with frameworks like PyTorch, TensorFlow, or XGBoost.
- Mindset: A growth mindset and excitement about breaking the status quo by seeking innovative solutions.

## Bonus

- Query optimization and SQL engine internals.
- Designing multi-tenant systems that handle sensitive enterprise data at scale.
- Developing search infrastructure for large-scale applications.

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**Apply:** https://hotfix.jobs/jobs/cfcfa4ed-3661-45be-8d97-71e231e17de7
**Canonical:** https://hotfix.jobs/jobs/cfcfa4ed-3661-45be-8d97-71e231e17de7