Intelligent Transportation Systems Engineer - AI & NLP

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Parsons is looking for an amazingly talented ITS Engineer (AI & NLP) to join our team! In this role you will support the Resident Engineer in all technical, administrative, and operational aspects related to the development, integration, testing, validation, and deployment of Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Generative AI, and Decision Support applications within the Advanced Traffic Management System (ATMS). The role includes overseeing AI-enabled traffic management functions, predictive analytics, incident detection and classification, traffic forecasting, operator assistance tools, chatbot and virtual assistant capabilities, knowledge management solutions, and AI-driven business intelligence platforms. The position requires reviewing system designs, algorithms, data architectures, training methodologies, model validation processes, cybersecurity requirements, and integration with ATMS and other ITS systems to ensure compliance with project requirements and successful operational deployment.

What You'll Be Doing:

Support and supervise ITS design input, specification compliance, installation, testing, and integration across major infrastructure projects, ensuring all works meet contractual and technical requirements. Review and recommend approval of FSDDs, shop drawings, material submittals, method statements, and test plans, while coordinating the installation of ITS devices, fiber networks, power systems, and related civil foundations. Conduct routine site inspections to verify workmanship, safety, and compliance with approved designs. Oversee and witness FAT, SAT, prototype tests, OTDR fiber tests, communication and power tests, and reliability testing, preparing and closing punch lists prior to handover. Maintain accurate documentation of approvals, changes, correspondence, and photographic records, supporting the Resident Engineer with variations, claims, as‑built verification, O&M documentation, and final system commissioning. 

Some of the principal responsibilities the AI & NLP Systems Engineer is required to perform are:

• Provide technical supervision of AI, ML, NLP, Large Language Model (LLM), predictive analytics, and decision-support system development and deployment activities.

• Review and recommend approval of Functional System Design Documents (FSDD), AI solution architectures, data models, AI governance plans, model development methodologies, and integration designs.

• Review and approve AI-related integration and testing plans, including model validation, performance testing, user acceptance testing, reliability testing, explainability assessments, and cybersecurity testing.

• Ensure the Contractor's compliance with the Contract Documents, approved AI development methodologies, data governance requirements, cybersecurity requirements, and applicable standards.

• Review and approve technical submittals related to AI platforms, NLP engines, knowledge management systems, LLM integrations, data analytics environments, and decision-support applications.

• Monitor the development and implementation of AI-enabled traffic management applications, including traffic prediction, incident detection, congestion analytics, operational recommendations, automated reporting, asset analytics, and performance monitoring solutions.

• Coordinate integration activities between AI systems, ATMS platforms, traffic databases, field ITS devices, video analytics systems, C-ITS platforms, enterprise systems, and external data sources.

• Review data quality, training datasets, model performance metrics, accuracy reports, bias assessments, and model improvement recommendations.

• Witness AI model demonstrations, prototype evaluations, proof-of-concept activities, validation exercises, and operational readiness testing.

• Support the Resident Engineer in evaluating Variation Orders, Change Orders, software enhancements, and system modifications related to AI and data analytics functions.

• Review issue logs, corrective action reports, model retraining plans, deployment roadmaps, and operational support procedures.

• Monitor AI solution deployment, release management, model version control, rollback procedures, and business continuity provisions.

• Attend all AI and NLP related meetings and prepare technical comments, recommendations, and meeting records.

• Review correspondence and prepare responses for signature.

• Maintain status logs for AI development, integration, testing, deployment, and issue resolution activities.

• Provide punch lists and final acceptance recommendations for AI-related deliverables.

• Review and approve as-built documentation, model documentation, data dictionaries, administrator manuals, operating procedures, training materials, and final handover documentation.

What Required Skills You'll Bring:

• Minimum 7 years of experience in software systems, intelligent transportation systems, data analytics, artificial intelligence, or digital transformation projects.

• Minimum 3 years of experience in AI, Machine Learning, Data Science, NLP, LLM, Advanced Analytics, or Decision Support System implementation projects.

• Bachelor's Degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Computer Engineering, Information Technology, or related discipline from an accredited institution.

• Strong understanding of:

  • Artificial Intelligence and Machine Learning technologies

  • Natural Language Processing (NLP) and Large Language Models (LLM)

  • Predictive analytics and forecasting systems

  • Intelligent Decision Support Systems

  • Data science methodologies and model lifecycle management

  • Data architecture, data governance, and data quality management

  • Enterprise software architecture and system integration

  • API integrations, databases, and cloud-based environments

  • MLOps, model training, deployment, monitoring, and version control

  • AI explainability, model validation, and performance measurement

  • Cybersecurity and secure AI implementation practices

  • Traffic management operations and ITS business processes

• Excellent knowledge of AI integration within transportation management, smart city, mobility, or operational technology environments.

• Strong understanding of business intelligence platforms, data visualization, dashboard development, and reporting solutions.

• Experience with AI-enabled video analytics, traffic prediction, incident detection, knowledge management systems, or transportation analytics is highly desirable.

• Familiarity with cloud, virtualized, and hybrid computing environments.

• Experience in supervision of enterprise AI deployment and large-scale software integration projects.

• Knowledge of RTA ITS systems, ATMS platforms, and transportation operations is highly desirable.

• Strong coordination, stakeholder management, documentation, and technical review capabilities.

• Excellent written and verbal communication skills.

• Professional certifications in AI, Data Science, Cloud Technologies, Analytics, or Systems Engineering are considered an advantage.

• Arabic language capability is a plus.