Description

Job Summary:
The Artificial Intelligence (AI) Engineer will design, develop, and deploy AI/ML solutions that enhance Bechtel’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. 

Major Responsibilities:
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. 
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. 
Deploy AI models on cloud platforms (Azure AI/ML, Databricks) and integrate with Bechtel’s digital ecosystem. 
Implement MLOps practices for lifecycle management, monitoring, and continuous improvement. 
Work with cross-functional teams (engineering, IT, project controls) to align AI solutions with business objectives. 
Communicate complex AI concepts to non-technical stakeholders. 
Ensure AI solutions adhere to Bechtel’s security, ethics, and compliance standards. 
Maintain documentation for models, processes, and decision-making. 
Stay current with emerging AI technologies (e.g., agentic AI, multimodal systems). 
Contribute to Bechtel’s AI Center of Excellence initiatives and innovation programs. 

Requirements

Education and Experience Requirements:
Requires bachelor’s degree in Computer Science, Data Science, Engineering, or related field (Master's degree preferred) and 5-8+ years of relevant experience in AI/ML development OR 9-12 years of related work experience.

Required Knowledge and 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.
Understanding of engineering and construction workflows is a plus.
Strong problem-solving, communication, and collaboration 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.