Senior AI Engineer - Professional Services

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

Job Description:

DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business - today and in the future.

Key Responsibilities:

• Partner with Customers: Collaborate closely with customer stakeholders to understand their business goals, identify high-impact use cases, and define technical requirements for AI solutions.
• Build & Deploy AI Solutions: Design, develop, and deploy end-to-end AI solutions using the DataRobot platform and open-source tools. This includes:
  • Agentic AI: Developing and deploying agents on DataRobot leveraging common frameworks such as Langgraph, CrewAI, Llama Index
  • Generative AI: Building custom GenAI chatbots, Retrieval-Augmented Generation (RAG) systems.
  • Predictive AI: Developing and deploying classic machine learning models for use cases like forecasting, churn prediction, and fraud detection.
• Serve as a Technical Expert: Act as a subject matter expert on the DataRobot platform and modern AI/ML development, guiding customers on best practices for MLOps, model governance, and scaling AI initiatives.
• Deliver Value: Ensure that the solutions you build are robust, scalable, and directly contribute to the customer's business objectives.
• Communicate & Collaborate: Clearly communicate complex technical concepts and project outcomes to both technical and non-technical audiences, from data scientists to C-level executives.

Knowledge, Skills and Abilities:

AI & Machine Learning Expertise:

• Strong proficiency in Python and common data science libraries (e.g., pandas, scikit-learn, NumPy, etc.).
• Practical experience with Generative AI technologies, including Large Language Models (LLMs), vector databases,
• Solid understanding of the end-to-end agentic AI lifecycle from building agents in frameworks like LangGraph or CrewAI, to at scale deployment and monitoring.

Application Development & Operations:

• Demonstrable experience developing and deploying applications, including building REST APIs (e.g., using Flask, FastAPI) to serve ML models and GenAI logic.
• Proficiency with containerization using Docker and experience deploying and managing applications on container orchestration platforms like Kubernetes (K8s).
• Solid understanding of secure application development practices, including authentication/authorization (e.g., OAuth, API keys), secrets management, and securing public-facing endpoints.
• Customer Focus: Experience in a client-facing or consulting role with exceptional verbal and written communication skills. You must be comfortable leading technical discussions and presenting to diverse audiences.
• Problem-Solving Mindset: A deep curiosity and a passion for solving complex, unstructured problems.

Requisite Education and Experience / Minimum Qualifications:

• Experience: Approximately 6-8 years of hands-on experience in AI Application development, software engineering, machine learning engineering, or a similar role with a proven track record of deploying AI solutions or applications into production.
• Education: A Master's Degree or Ph.D. in Computer Science, Statistics, Artificial Intelligence, Engineering, or a related quantitative field.
• Cloud Experience: Hands-on experience with a major cloud platform (AWS, Azure, or GCP).
• DataRobot Experience: Familiarity with the DataRobot AI Platform is a strong plus.
• MLOps Knowledge: Understanding of MLOps principles and tools for model CI/CD, monitoring, and governance.

Compensation Statement

The U.S. annual on-target earnings (OTE) range for this full-time position is between $165,000 and $225,000 USD/year. This range represents a combination of annual base pay and targeted commission. Actual offers may be higher or lower than this range based on various factors, including (but not limited to) the candidate's wo