AI Engineer

Machine Learning Technologies, LLC; Houston (TX); On-site; USD 120,000 - 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 work on RAG architectures, custom AI agents, document intelligence, and model serving to support real-world business use cases.

Collaborate with data engineers and developers to deliver end-to-end AI-powered products, implement evaluation frameworks, governance, and observability, and drive production deployment on Azure or AWS.

Qualifications

• Hands-on experience building enterprise GenAI solutions.
• Familiar with retrieval augmented generation and vector search.
• Experience deploying in regulated or enterprise environments.

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 solution quality, accuracy, and reliability.
• Design prompts and optimize prompt engineering strategies.
• Deploy and manage models using Databricks Model Serving and related MLOps capabilities.
• 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

Custom AI agents

Information extraction

Model serving

AI governance

Tools

Databricks Model Serving

Unity Catalog

Lakehouse architecture

Job description

We are seeking an AI Engineer with hands‑on experience designing, building, and deploying enterprise Generative AI solutions on Databricks. The ideal candidate will have expertise in RetrievalAugmented Generation (RAG), custom AI agents, document intelligence, vector search, evaluation frameworks, prompt engineering, and model serving. The role involves working closely with business and technical stakeholders to develop scalable AI solutions that support real‑world enterprise use cases.

Key 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 solution quality, accuracy, and reliability.
• Design prompts and optimize prompt engineering strategies.
• Deploy and manage models using Databricks Model Serving and related MLOps capabilities.
• 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.

Required Skills:

AI / GenAI

• Custom AI agents / Agentic workflows
• Information extraction and AI document parsing
• Model serving and inference APIs
• AI governance and quality assessment

Databricks :

• Databricks Model Serving
• Unity Catalog
• Lakehouse architecture

Technical Stack :

• LangChain / LangGraph / Semantic Kernel (preferred)
• Azure and/or AWS

Preferred Qualifications :

• Experience deploying GenAI applications in regulated or enterprise environments.
• Databricks certifications (Machine Learning, GenAI, Lakehouse Fundamentals).
• Experience with multi‑agent systems and enterprise AI architectures.
• Strong understanding of evaluation, observability, and governance of AI solutions.

Ideal Candidate Profile:

• Hands‑on RAG and vector search implementation.
• AI evaluation and governance frameworks.
• Production deployment experience on Azure and/or AWS.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.