AI Engineer :: Hybrid in Dallas, TX :: Face to Face Interview

Title: AI Engineer

Hybrid in Dallas, TX

6+ Months

Face to Face Interview

Job Summary:

The AI Engineer is responsible for designing, developing, deploying, and optimizing artificial intelligence and machine learning solutions that drive business innovation and operational efficiency. This role partners with cross-functional teams to build scalable AI applications, integrate generative AI capabilities into enterprise platforms, and deploy production-ready machine learning models. The ideal candidate has experience with modern AI technologies, cloud-based AI services, MLOps, and software engineering best practices, along with a passion for leveraging emerging AI capabilities to solve complex business problems.

Responsibilities:

• Design, develop, deploy, and maintain scalable AI and machine learning solutions for enterprise business applications.
• Build and integrate Generative AI and Large Language Model (LLM) solutions to enhance business processes and user experiences.
• Develop AI-powered applications, APIs, and services using Python and modern AI frameworks.
• Design, train, evaluate, deploy, and optimize machine learning models for production environments.
• Implement Retrieval-Augmented Generation (RAG), prompt engineering techniques, vector databases, and AI agent frameworks where appropriate.
• Deploy and manage AI solutions using cloud-based AI services, with a preference for Microsoft Azure.
• Monitor model performance, optimize inference, and implement continuous improvements to ensure accuracy, scalability, and reliability.
• Collaborate with data engineers, software developers, and business stakeholders to integrate AI solutions with enterprise data platforms and applications.
• Implement MLOps best practices, including model versioning, CI/CD pipelines, automated testing, model evaluation, and production monitoring.
• Utilize containerization and orchestration technologies such as Docker and Kubernetes to deploy scalable AI workloads.
• Work with SQL and enterprise data sources to prepare, process, and integrate data for AI and machine learning solutions.
• Troubleshoot complex technical issues across distributed cloud environments and optimize system performance.
• Research emerging AI technologies and industry best practices, recommending innovative solutions that create business value.
• Participate in Agile development processes, providing technical leadership and collaborating with cross-functional teams throughout the software development lifecycle.

Requirements:

• 5+ years of experience in software engineering, machine learning, artificial intelligence, or related technical roles.
• 3+ years of experience developing and deploying production AI/ML solutions.
• Hands-on experience with Large Language Models (LLMs), Generative AI, and modern AI frameworks.
• Strong Python programming skills with experience building scalable AI applications and APIs.
• Experience with model deployment, optimization, monitoring, and cloud-based AI services.
• Experience designing, building, and optimizing machine learning models to solve business challenges.
• Knowledge of Retrieval-Augmented Generation (RAG), prompt engineering, vector databases, and AI agent frameworks.
• Familiarity with MLOps practices, including model versioning, CI/CD, model evaluation, and monitoring.
• Experience with Docker and Kubernetes for containerization and orchestration.
• Working knowledge of SQL, data processing, and enterprise data platform integration.
• Strong analytical and problem-solving skills in distributed cloud environments.
• Ability to evaluate and apply emerging AI/ML technologies and industry best practices.
• Excellent communication, collaboration, stakeholder management, and Agile development experience.
• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.

Preferred Requirements:

• Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
• Experience with Microsoft Azure AI services, Azure Machine Learning, or comparable cloud AI platforms.
• Experience with Generative AI, LLMs, and enterprise AI application development.