{"schemaVersion":"jobsearcher.job.v1","id":"125a901eefca26e681f93425","url":"https://jobsearcher.com/jobs/125a901eefca26e681f93425","canonicalUrl":"https://jobsearcher.com/jobs/125a901eefca26e681f93425","title":"Artificial Intelligence Technical Lead","description":"We are seeking an experienced Subject Matter Expert in Artificial Intelligence. This person shall provide technical Artificial Intelligence (AI) expertise and support services required to advance NWS priorities in science, research, policy, program management, and strategic implementation.\nThey will serve as the technical lead for AI initiatives, overseeing solution architecture, project delivery, AI/ML development, DevSecOps/MLOps practices, and stakeholder collaboration to advance enterprise AI capabilities.\nThis support shall include, but is not limited to, the following tasks:\nDuties:\nUser Needs and Technical Project Management Support\nTranslates complex operational, scientific, and business challenges and user feedback into actionable technical requirements, system architectures, and implementation plans for AI-driven solutions.\nOversees the lifecycle of AI initiatives from a technical perspective by prioritizing features that maximize organizational value while managing resource constraints and risks.\nCoordinates between cross-functional teams to ensure that project milestones and AI solutions align with enterprise architecture and cybersecurity requirements as well as meet both technical benchmarks and user expectations.\nTechnical Consultation and Architecture\nProvides expert guidance to development teams on AI/ML architectural design, software engineering practices, data pipelines, model selection, deployment strategies, and the implementation of best practices, including testing and maintenance.\nConducts rigorous technical assessments and architecture reviews of proposed and ongoing AI projects to assess feasibility, scalability, security, performance standards, operational readiness, and risk.\nIdentifies potential technical bottlenecks and ethical considerations in AI workflows and recommends proactive solutions to timely and responsible delivery.\nRecommend and implement best practices for software engineering, Development, Security, and Operations (DevSecOps), Machine Learning Operations (MLOps), testing, monitoring, observability, and lifecycle management of AI systems.\nTechnical Development\nLeads the end-to-end development of AI projects for NWS enterprise priorities that do not have a development team, ensuring they are built for production-grade reliability and scalability.\nImplement and support Continuous Integration and Continuous Deployment (CI/CD), DevSecOps, and MLOps practices, including automated testing, model versioning, deployment automation, monitoring, and incident response.\nTroubleshoot operational issues, performance bottlenecks, and deployment challenges associated with AI systems and supporting infrastructure.\nSupports the development of proof-of-concepts to test emerging AI technologies and their potential application within the enterprise.\nCommunications\nDistills sophisticated AI architectures, concepts, engineering challenges, and model performance metrics into clear, non-technical insights for executive leadership and stakeholders.\nPrepare technical documentation, implementation plans, architecture diagrams, deployment guidance, and operational support materials.\nFacilitates dialogue between developers, data scientists, engineers, and product owners to maintain clarity on project goals and ensure continuous feedback.\nSupports the communication of current NWS AI capabilities as well as future AI opportunities, presenting technical progress, operational risks, strategic wins, and possibilities in formal reports and briefings.\nRecommend explicitly referencing Development, Security, and Operations (DevSecOps) and Machine Learning Operations (MLOps) practices. These terms communicate that the role is expected to support the operationalization of AI capabilities, including automated deployment pipelines, model versioning, security controls, monitoring, observability, and ongoing maintenance.\nExperience:\nBachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Technology, or related field.\nMinimum 7-10 years of experience in software engineering, systems architecture, data science, or related technical fields.\nMinimum 5 years of experience designing, developing, and implementing AI/ML solutions in production environments.\nExperience leading complex technical projects involving cross-functional teams and stakeholders.\nAbility to obtain and maintain a Public Trust or other required federal security clearance.\nDemonstrated experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.\nExperience developing and deploying machine learning models in cloud environments such as AWS, Azure, or Google Cloud.\nStrong knowledge of DevSecOps, MLOps, CI/CD pipelines, and software development lifecycle best practices.\nExperience designing scalable system architectures and data pipelines.\nProficiency in Python and other relevant programming languages.\nExperience implementing monitoring, testing, version control, and operational support for AI systems.\nT6HdpcTwv2","company":"Joint Technology Solution","rawCompany":"joint technology solution","city":"Remote","state":"OR","isRemote":false,"isActive":false,"createdAt":"2026-08-12T12:57:31.904Z","occupations":[{"code":"11-3021.00","title":"Computer and Information Systems Managers","slug":"computer-and-information-systems-managers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"},{"code":"15-1299.09","title":"Information Technology Project Managers","slug":"information-technology-project-managers"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541690","title":"Other Scientific and Technical Consulting Services","slug":"other-scientific-and-technical-consulting-services"},{"code":"541990","title":"All Other Professional, Scientific, and Technical Services","slug":"all-other-professional-scientific-and-technical-services"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Artificial Intelligence Technical Lead","description":"We are seeking an experienced Subject Matter Expert in Artificial Intelligence. This person shall provide technical Artificial Intelligence (AI) expertise and support services required to advance NWS priorities in science, research, policy, program management, and strategic implementation.\nThey will serve as the technical lead for AI initiatives, overseeing solution architecture, project delivery, AI/ML development, DevSecOps/MLOps practices, and stakeholder collaboration to advance enterprise AI capabilities.\nThis support shall include, but is not limited to, the following tasks:\nDuties:\nUser Needs and Technical Project Management Support\nTranslates complex operational, scientific, and business challenges and user feedback into actionable technical requirements, system architectures, and implementation plans for AI-driven solutions.\nOversees the lifecycle of AI initiatives from a technical perspective by prioritizing features that maximize organizational value while managing resource constraints and risks.\nCoordinates between cross-functional teams to ensure that project milestones and AI solutions align with enterprise architecture and cybersecurity requirements as well as meet both technical benchmarks and user expectations.\nTechnical Consultation and Architecture\nProvides expert guidance to development teams on AI/ML architectural design, software engineering practices, data pipelines, model selection, deployment strategies, and the implementation of best practices, including testing and maintenance.\nConducts rigorous technical assessments and architecture reviews of proposed and ongoing AI projects to assess feasibility, scalability, security, performance standards, operational readiness, and risk.\nIdentifies potential technical bottlenecks and ethical considerations in AI workflows and recommends proactive solutions to timely and responsible delivery.\nRecommend and implement best practices for software engineering, Development, Security, and Operations (DevSecOps), Machine Learning Operations (MLOps), testing, monitoring, observability, and lifecycle management of AI systems.\nTechnical Development\nLeads the end-to-end development of AI projects for NWS enterprise priorities that do not have a development team, ensuring they are built for production-grade reliability and scalability.\nImplement and support Continuous Integration and Continuous Deployment (CI/CD), DevSecOps, and MLOps practices, including automated testing, model versioning, deployment automation, monitoring, and incident response.\nTroubleshoot operational issues, performance bottlenecks, and deployment challenges associated with AI systems and supporting infrastructure.\nSupports the development of proof-of-concepts to test emerging AI technologies and their potential application within the enterprise.\nCommunications\nDistills sophisticated AI architectures, concepts, engineering challenges, and model performance metrics into clear, non-technical insights for executive leadership and stakeholders.\nPrepare technical documentation, implementation plans, architecture diagrams, deployment guidance, and operational support materials.\nFacilitates dialogue between developers, data scientists, engineers, and product owners to maintain clarity on project goals and ensure continuous feedback.\nSupports the communication of current NWS AI capabilities as well as future AI opportunities, presenting technical progress, operational risks, strategic wins, and possibilities in formal reports and briefings.\nRecommend explicitly referencing Development, Security, and Operations (DevSecOps) and Machine Learning Operations (MLOps) practices. These terms communicate that the role is expected to support the operationalization of AI capabilities, including automated deployment pipelines, model versioning, security controls, monitoring, observability, and ongoing maintenance.\nExperience:\nBachelor's degree in Computer Science, Data Science, Artificial Intelligence, Software Engineering, Information Technology, or related field.\nMinimum 7-10 years of experience in software engineering, systems architecture, data science, or related technical fields.\nMinimum 5 years of experience designing, developing, and implementing AI/ML solutions in production environments.\nExperience leading complex technical projects involving cross-functional teams and stakeholders.\nAbility to obtain and maintain a Public Trust or other required federal security clearance.\nDemonstrated experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar technologies.\nExperience developing and deploying machine learning models in cloud environments such as AWS, Azure, or Google Cloud.\nStrong knowledge of DevSecOps, MLOps, CI/CD pipelines, and software development lifecycle best practices.\nExperience designing scalable system architectures and data pipelines.\nProficiency in Python and other relevant programming languages.\nExperience implementing monitoring, testing, version control, and operational support for AI systems.\nT6HdpcTwv2","datePosted":"2026-08-12T12:57:31.904Z","dateModified":"2026-08-12T12:57:31.904Z","hiringOrganization":{"@type":"Organization","name":"Joint Technology Solution","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Remote","addressRegion":"OR","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"125a901eefca26e681f93425"},"url":"https://jobsearcher.com/jobs/125a901eefca26e681f93425"}}