Senior AI Engineer — GenAI, MLOps & Customer Impact

DataRobot; Texas; On-site; USD 165,000 - 225,000; Full time

Job summary

DataRobot in Texas is seeking an experienced AI Applications Engineer to design, develop, and deploy end-to-end AI solutions on the DataRobot platform. You will collaborate with customers to define requirements, build GenAI and predictive models, and ensure scalable, secure production deployments.

The role requires 6–8 years in AI application development, strong Python skills, cloud experience (AWS/Azure/GCP), and hands-on MLOps knowledge.

Qualifications

• Approximately 6–8 years of hands-on experience in AI Application development, software engineering, ML engineering, or similar with proven deployment track record.
• Master's Degree or Ph.D. in Computer Science, Statistics, AI, Engineering, or related quantitative field.
• Hands-on cloud experience with AWS, Azure, or GCP.

Responsibilities

• Partner with customers to understand business goals and define technical requirements for AI solutions.
• Build and deploy end-to-end AI solutions using DataRobot platform and open-source tools (GenAI, predictive AI, agentic AI).
• Serve as SME on DataRobot platform, guiding customers on MLOps, model governance, and scaling AI initiatives.
• Deliver robust, scalable solutions that directly contribute to customer objectives.
• Communicate complex concepts clearly to both technical and non-technical audiences.

Skills

Python

Generative AI

REST APIs

Docker

Kubernetes

Cloud platforms

MLOps

Communication

Education

Master's degree

Ph.D.

Tools

LangGraph

CrewAI

Llama Index

Flask

FastAPI

Docker

Kubernetes

Job description

DataRobot in Texas is seeking an experienced AI Applications Engineer to design, develop, and deploy end-to-end AI solutions on the DataRobot platform. You will collaborate with customers to define requirements, build GenAI and predictive models, and ensure scalable, secure production deployments.

The role requires 6–8 years in AI application development, strong Python skills, cloud experience (AWS/Azure/GCP), and hands-on MLOps knowledge.