ITS Engineer (AI & NLP)

In a world of possibilities, pursue one with endless opportunities. Imagine Next! At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible. Job Description: In a world of possibilities, pursue one with endless opportunities. Imagine Next! At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible. 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

Note: The posting does not clearly separate a dedicated Requirements / Qualifications section. It describes responsibilities and principal responsibilities, but there is no explicit list under a distinct 'Requirements' heading. From the content, the role requires deep involvement with AI, ML, NLP, LLM, predictive analytics, AI governance, data governance, cybersecurity, integration with ATMS/ITS, and experience reviewing design documents, testing plans, and similar activities. Based on this, hard requirements inferred include: experience supervising AI/ML/NLP/LLM deployment; ability to review AI solution architectures and data models; familiarity with AI governance and model validation; understanding of cybersecurity testing for AI systems; experience coordinating AI-enabled traffic management projects. However, since the prompt requires returning only explicit distinct requirements, this field is returned as null.

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. Principal responsibilities include: provide technical supervision of AI, ML, NLP, LLM, predictive analytics, and decision-support system development and deployment activities; review and approve 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 compliance with 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.