Senior AI Data Engineer - RAG & LLM Infra

Cooley AI; Los Angeles (CA); On-site; USD 220,000 - 250,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

Health savings account

Paid time off 21 days

Job summary

Cooley AI is seeking a Senior AI Data Engineer to design and maintain production-grade AI infrastructure powering the firm’s AI-enabled data applications on the Northstar Lakehouse. You will lead RAG pipelines, embedding infrastructure, and LLM integration patterns, working with the Data Products squad to ensure reliability at scale.

The role emphasizes production engineering depth, observability, and governance, with collaboration across data, platform, and product teams in a fast-paced legal

Qualifications

• 5+ years of data engineering or AI engineering with hands-on production responsibility for RAG pipelines and LLM features.
• Strong experience with production-grade AI infrastructure and data pipelines.
• Proficient in Python and modern data tooling; comfortable in cloud data platforms.
• Experience with Databricks stack (Delta Lake, Unity Catalog, Model Serving).
• Familiarity with LLM APIs, prompt patterns, and observability practices.

Responsibilities

• Design, build, and maintain production RAG pipelines for retrieval and indexing.
• Own vector search implementation, embedding pipelines, and retrieval quality monitoring.
• Collaborate with Data Engineering & Platform teams to ensure governed data sources.
• Implement LLM integration patterns, observability, and cost-aware API usage.
• Contribute to AI feature roadmap and maintain production-grade reliability.

Skills

Python proficiency

AI engineering

RAG pipelines

LLM integration

Agile delivery

Tools

Databricks

Delta Lake

Unity Catalog

Databricks Vector Search

Pinecone/Chroma

Job description

Cooley AI is seeking a Senior AI Data Engineer to design and maintain production-grade AI infrastructure powering the firm’s AI-enabled data applications on the Northstar Lakehouse. You will lead RAG pipelines, embedding infrastructure, and LLM integration patterns, working with the Data Products squad to ensure reliability at scale.

The role emphasizes production engineering depth, observability, and governance, with collaboration across data, platform, and product teams in a fast-paced legal