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Job Summary
The
Artificial Intelligence Engineer
will design, develop, and deploy AI/ML solutions that enhance the client's engineering, construction, and business processes. This role bridges advanced technology and practical application, ensuring AI systems deliver measurable value across projects and functions. The position requires strong technical expertise in AI and machine learning, combined with an understanding of engineering workflows and data governance.
Key Responsibilities
AI Solution Development
Design, build, and implement AI/ML models for predictive analytics, generative design, and automation.
Convert prototypes into production-ready applications using frameworks like TensorFlow, PyTorch, or Scikit-learn.
Data Engineering & Integration
Collaborate with data engineers to develop robust data pipelines and architectures.
Apply ETL techniques and big-data tools to cleanse, organize, and transform data for AI models.
Deployment & Optimization
Deploy AI models on cloud platforms (Azure AI/ML, Databricks) and integrate with the client's digital ecosystem.
Implement MLOps practices for lifecycle management, monitoring, and continuous improvement.
Collaboration & Stakeholder Engagement
Work with cross-functional teams (engineering, IT, project controls) to align AI solutions with business objectives.
Communicate complex AI concepts to non-technical stakeholders.
Governance & Compliance
Ensure AI solutions adhere to the client's security, ethics, and compliance standards.
Maintain documentation for models, processes, and decision-making.
Innovation & Continuous Learning
Stay current with emerging AI technologies (e.g., agentic AI, multimodal systems).
Contribute to the client's AI Center of Excellence initiatives and innovation programs.
Job Dimensions
Works under minimal supervision with latitude for independent judgment.
Handles issues of diverse scope within defined parameters.
May act as a technical lead on small projects or initiatives.
Required Skills
Proficiency in
Python
and AI frameworks (TensorFlow, PyTorch).
Experience with cloud platforms (Azure AI stack, Databricks).
Knowledge of MLOps, containerization (Docker/Kubernetes), and CI/CD pipelines.
Strong problem-solving, communication, and collaboration skills.
Preferred Skills
Familiarity with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG).
Experience with knowledge graphs, agent-based AI systems, and predictive analytics.
Understanding of engineering and construction workflows.
Education Requirements
Bachelor's degree in Computer Science, Data Science, Engineering, or related field (required).
Master's degree preferred.
Required Experience
8-12 years of relevant experience in AI/ML development; or 12-15 years of related work experience without a degree.
Benefits
Medical, Vision, and Dental Insurance Plans
401k Retirement Fund
About the Client
This privately held
engineering, procurement, and construction
organization has been delivering some of the world's most complex and consequential infrastructure projects for more than 125 years - more than 25,000 projects across 160 countries on all seven continents. Clients include national governments, global energy companies, and the world's largest public agencies across sectors spanning energy and industrial, infrastructure, nuclear and environmental remediation, government services, and mining and metals. With a Glassdoor rating of 4.0 stars from nearly 2,500 employee reviews and 78 percent of employees recommending the company, the organization employs civil and structural engineers, project controls specialists, procurement managers, nuclear and environmental remediation professionals, and now technical roles in AI, data science, and enterprise systems who collaborate to deliver projects at a scale that is nearly impossible to find elsewhere.
About GTT
GTT is a minority-owned staffing firm and a subsidiary of Chenega Corporation, a Native American-owned company in Alaska. We highly value diverse and inclusive workplaces and support Fortune 500 organizations across banking, financial services, technology, life sciences, biotech, utilities, and retail sectors throughout the U.S. and Canada.