Senior AI Systems Engineer — Remote, Scalable Platforms

ContentBuffer; San Francisco (CA); Hybrid; USD 208,000 - 315,000; Full time

Job summary

Snorkel AI, Inc. is seeking a Senior Software Engineer in San Francisco, CA to build and operate large-scale AI data systems supporting frontier models and AI research labs. You will own architecture, design, and productionize back-end services powering AI workloads and evaluation pipelines.

You will collaborate with engineers, PMs, and field teams to deliver scalable AI data platforms, deploy agents, and drive performance improvements across distributed compute and data workflows.

Qualifications

• 4 years Java & TypeScript development with relational databases
• 4 years building large-scale distributed systems for data processing
• 3 years designing, developing AI/ML systems and services in production
• 3 years data storage, compute & retrieval for AI/ML applications
• 3 years improving LLM applications via evaluation frameworks and prompt engineering
• 3 years leading or owning delivery of large engineering projects

Responsibilities

• Own architecture, design, development, and operations of large-scale AI/ML systems
• Launch agents into production to run long, complex reasoning tasks
• Prototype, optimize, and maintain scalable back-end services for new tools
• Design extensible interfaces between internal services and storage layers
• Collaborate in a customer-focused, cross-functional environment

Skills

Java

TypeScript

Distributed systems

AI/ML systems

Cloud-native apps

RAG

MCP

LLM apps

Data storage

Data retrieval

Education

Bachelor’s degree in Computer Science or related field

Job description

Snorkel AI, Inc. is seeking a Senior Software Engineer in San Francisco, CA to build and operate large-scale AI data systems supporting frontier models and AI research labs. You will own architecture, design, and productionize back-end services powering AI workloads and evaluation pipelines.

You will collaborate with engineers, PMs, and field teams to deliver scalable AI data platforms, deploy agents, and drive performance improvements across distributed compute and data workflows.