Enterprise GenAI Engineer - RAG & Vector Search

MACHINE LEARNING TECHNOLOGIES LLC; Houston (TX); On-site; USD 150,000 - 190,000; Full time

Job summary

MACHINE LEARNING TECHNOLOGIES LLC in Houston is seeking an AI Engineer to design, build, and deploy enterprise Generative AI solutions on Databricks. You will lead RAG architectures, custom AI agents, document intelligence, and model serving in collaboration with data engineers and full-stack developers.

The role emphasizes production deployment, governance, and observability in enterprise environments, with Databricks certifications and cloud-native deployments on Azure/AWS as valuable assets.

Qualifications

• Hands-on experience delivering enterprise GenAI solutions.
• Experience deploying GenAI in regulated environments is a plus.
• Databricks certifications (ML, GenAI, Lakehouse Fundamentals) are valued.

Responsibilities

• Design and implement Generative AI and Agentic AI solutions.
• Build and optimize RAG architectures and vector search solutions.
• Develop custom AI agents and agent workflows.
• Implement document parsing, information extraction, and document intelligence capabilities.
• Create and maintain evaluation frameworks to assess AI quality, accuracy, and reliability.
• Design prompts and optimize prompt engineering strategies.
• Deploy and manage models using Databricks Model Serving and related MLOps.
• Integrate AI solutions with enterprise data platforms and applications.
• Collaborate with Data Engineers and Full Stack Developers to deliver end-to-end AI-powered products.

Skills

RAG

Custom AI agents

Prompt engineering

Evaluation frameworks

Information extraction

Vector search

Model serving

AI governance

Tools

Databricks AI/ML Platform

Databricks Model Serving

MLflow

Delta Lake

Vector Search

Unity Catalog

PySpark

Databricks SQL

Lakehouse architecture

Job description

MACHINE LEARNING TECHNOLOGIES LLC in Houston is seeking an AI Engineer to design, build, and deploy enterprise Generative AI solutions on Databricks. You will lead RAG architectures, custom AI agents, document intelligence, and model serving in collaboration with data engineers and full-stack developers.

The role emphasizes production deployment, governance, and observability in enterprise environments, with Databricks certifications and cloud-native deployments on Azure/AWS as valuable assets.