Artificial Intelligence (AI) Engineer

Description

We are looking for an Artificial Intelligence (AI) Engineer to join a Long-term Contract opportunity based in Houston, Texas. This position will focus on creating practical AI solutions that improve business outcomes, from model development through production support. The role blends hands-on engineering with cross-functional collaboration, helping teams adopt AI tools effectively while maintaining strong standards for privacy, security, and reliability.

Responsibilities:
Build, test, and operationalize machine learning and predictive analytics solutions, ensuring they perform reliably from initial development through production use.
Create and support data pipelines and system integrations that supply clean, usable data for AI models and related applications.
Work with business stakeholders to define use cases, shape AI-driven workflows, and launch solutions using modern AI platforms and assistants.
Provide end-user guidance through training sessions, practical documentation, and direct support so teams can apply AI tools with confidence.
Act as a trusted internal advisor on applied AI by reviewing new technologies and identifying opportunities where they can deliver measurable business value.
Convert business challenges into scalable technical approaches and present findings clearly to both technical teams and non-technical audiences.
Promote responsible AI practices by emphasizing data protection, model quality, governance, and secure usage across initiatives.
Collaborate with IT, data, and operational teams to prioritize, develop, and implement AI projects that align with organizational goals.
Take on additional assignments as needed to support evolving project and business priorities.

Requirements

Demonstrated experience developing, validating, and deploying machine learning models using real-world business data.
Strong Python programming skills, including hands-on use of libraries such as pandas, NumPy, scikit-learn, and either TensorFlow or PyTorch.
Knowledge of AI assistants and workflow tools, including prompt design, evaluation methods, and business process integration.
Experience with production model deployment, performance tracking, and MLOps practices that support stability and version control.
Ability to design and maintain data pipelines within cloud or enterprise environments, with exposure to Microsoft Azure preferred.
Solid understanding of relational databases and data transformation techniques used to prepare data for AI and analytics solutions.
Familiarity with computer vision, detection models, or related AI applications is beneficial.
Strong collaboration and communication skills, with the ability to work effectively across technical and business teams.

Technology Doesn't Change the World, People Do.

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