AI Engineer

Position Summary

The Artificial Intelligence Engineer will design, develop, and deploy AI/ML solutions that enhance 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.

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 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 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 AI Center of Excellence initiatives and innovation programs.

Qualifications

Education:

• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field.
• Master’s degree preferred.

Experience:

• 8–12 years of relevant experience in AI/ML development or 12–15 years of related work experience without a degree.

Technical 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.

Domain Knowledge:

• Understanding of engineering and construction workflows is a plus.

Soft Skills:

• 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.

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.