Remote GenAI Engineer - Production AI for Enterprises

Databricks; Boston (MA); On-site; USD 153,000 - 210,000; Full time

Job summary

Databricks seeks an AI Engineer - FDE to design, build, and deploy production GenAI and LLM applications for customers. This remote-friendly role focuses on delivering high-impact AI solutions with Databricks AI research.

You will own end-to-end deployments, collaborate with product and engineering, present at events, and occasionally travel to meet customers. A graduate degree or equivalent experience and hands-on cloud ML deployment skills are expected.

Qualifications

• Experience building GenAI applications with RAG, multi-agent systems, and fine-tuning.
• Experience deploying production-grade ML/GenAI on cloud providers.
• Hands-on data science experience with pandas, scikit-learn, PyTorch.
• Experience with Databricks Intelligence Platform and Apache Spark preferred.
• Willing to travel every 4-8 weeks to meet customers.

Responsibilities

• Develop cutting-edge GenAI solutions leveraging Databricks AI research.
• Own production rollouts of GenAI applications for customers.
• Serve as a trusted technical advisor across domains.
• Present at conferences like Data + AI Summit and others.
• Collaborate with product and engineering to influence priorities and roadmap.

Skills

GenAI apps

RAG

Multi-agent systems

Text2SQL

Fine-tuning

HuggingFace

LangChain

DSPy

Production-grade deployments

Cloud deployments

AWS/Azure/GCP

Presentation skills

Travel readiness

Education

Graduate degree in CS/Engineering/Statistics

Tools

Databricks Platform

Apache Spark

AWS

Azure

GCP

Job description

Databricks seeks an AI Engineer - FDE to design, build, and deploy production GenAI and LLM applications for customers. This remote-friendly role focuses on delivering high-impact AI solutions with Databricks AI research.

You will own end-to-end deployments, collaborate with product and engineering, present at events, and occasionally travel to meet customers. A graduate degree or equivalent experience and hands-on cloud ML deployment skills are expected.