• Embed with strategic enterprise accounts to map business-critical marketing and web workflows • Architect and implement agentic workflows using Webflow APIs, CMS, components, and emerging AI capabilities • Build integrations between Webflow and external platforms (ad platforms, analytics, CRM, DAM, data pipelines) • Implement human-in-the-loop safeguards, observability, rollback paths, and permission boundaries from day one • Ensure every deployment can survive production traffic, governance scrutiny, and real constraints without FDE involvement • Document where agentic workflows break down and identify which friction is systemic vs. customer-specific • Produce reusable architecture blueprints, reference implementations, and documented anti-patterns after every engagement • Engage pre-sale to de-risk complex AI or integration concerns for strategic accounts

• Create detailed multi-view production drawings from conceptual specifications, rough sketches, and architectural drawings • Produce 3D isometric renderings for client-facing presentations and internal engineering review • Translate high-level design intent into precise, dimensioned shop drawings that production teams can execute without ambiguity • Ensure all drawings meet manufacturing tolerances and machining requirements • Break down assemblies into individual components and sub-components with accurate part numbering • Generate complete bills of materials for each job including vendor references, part descriptions, quantities, and hardware specifications • Produce exploded assembly diagrams and component-level documentation to support in-house assembly and packaging • Maintain accuracy across BOMs as designs evolve through revisions • Prepare cut-ready DXF files for handoff to machine programmers and CNC production equipment teams • Ensure file accuracy, layer organization, and geometry cleanliness before every handoff • Work directly with AlphaCAM for programming support as needed • Coordinate with production teams to resolve any file or drawing issues before they reach the floor • Support the team in clearing an active production and engineering backlog efficiently • Maintain organized drawing files, revision histories, and project documentation • Flag discrepancies between design intent and producibility early in the process

Riverside Overview Riverside Research is an independent National Security Nonprofit dedicated to research and development in the national interest. We provide high-end technical services, research and development, and prototype solutions to some of the country’s most challenging technical problems. All Riverside Research opportunities require U.S. Citizenship. Position Overview Riverside Research's Cognitive Intelligence Solutions Group (CISG) is seeking a Remote Sensing Engineer to support cutting-edge geospatial intelligence, autonomous sensing, and AI/ML-driven data exploitation efforts for the U.S. Department of Defense and Intelligence Community. The successful candidate will serve as a technical lead responsible for the automated verification and validation (V&V), test and evaluation (T&E), and performance assessment of remote sensing data pipelines, AI/ML models, and third-party vendor capabilities. This role bridges rigorous scientific methodology with production-grade engineering, enabling CISG to deliver validated, mission-ready geospatial intelligence products. The ideal candidate combines deep expertise in multispectral and hyperspectral remote sensing with hands-on experience applying machine learning to operational geospatial workflows. Responsibilities - Design, develop, and implement automated V&V and T&E frameworks to assess the accuracy, performance, and operational readiness of remote sensing data products, AI/ML models, and vendor-delivered geospatial capabilities. - Lead the technical evaluation of commercial and government remote sensing platforms, sensors (multispectral, hyperspectral, SAR, LiDAR), and associated data products against mission-specific requirements. - Develop and maintain scalable, production-grade machine learning pipelines for geospatial applications including change detection, land cover classification, object detection, and environmental monitoring. - Apply state-of-the-art AI/ML techniques — including deep learning, transfer learning, self-supervised learning, and large vision/language models — to automate remote sensing data exploitation and analysis workflows. - Conduct rigorous uncertainty quantification, validation metric development, and statistical performance benchmarking across multi-source, multi-temporal geospatial datasets. - Architect and execute data quality assessment (DQA) protocols for ingested satellite, airborne, and in-situ sensor data; document and communicate findings to program teams and stakeholders. - Collaborate with program managers, government customers, and interdisciplinary engineering teams to translate operational requirements into validated technical solutions. - Evaluate and integrate emerging remote sensing technologies and open-source AI/ML frameworks; assess vendor claims, algorithm documentation, and technical data packages. - Contribute to IRAD initiatives advancing CISG's remote sensing and autonomous sensing capabilities, including development of novel approaches for environmental monitoring, target detection, and geospatial change analytics. - Author technical reports, white papers, and briefings documenting methodology, V&V results, and performance findings for government sponsors. - Provide technical mentorship to junior engineers and researchers on remote sensing methods, ML best practices, and geospatial data science. - Stay current with advances in foundation models, multi-modal geospatial AI, and emerging remote sensing sensor modalities relevant to national security applications. Qualifications Required Qualifications: - Active U.S. Citizenship (required for all Riverside Research positions). - Must be able to obtain and maintain a Top Secret security clearance with SCI access; ability to obtain program-specific clearances as required. Candidates with an active TS/SCI are strongly preferred. - Bachelor's degree in Remote Sensing, Geospatial Science, Earth Systems, Electrical Engineering, Computer Science, or a closely related STEM field. - A minimum of 8 years of related experience with a Bachelor's degree, 6 years with a Master's degree, 3 years with a PhD, or equivalent combination of education and experience. Graduate research experience counts toward this threshold. - Demonstrated expertise in multispectral and/or hyperspectral remote sensing data analysis, including atmospheric correction, spectral indices, spectral unmixing, and feature extraction. - Proficiency in Python for geospatial data engineering, including experience with rasterio, rioxarray, xarray, GDAL, geopandas, NumPy, and scikit-learn. - Hands-on experience with machine learning and statistical modeling applied to remote sensing or geospatial datasets (e.g., classification, regression, anomaly detection, change detection). - Experience developing and executing V&V or T&E processes for data products, software systems, or AI/ML models, including design of test plans, performance metrics, and acceptance criteria. - Familiarity with geospatial platforms and tools: ArcGIS Pro, QGIS, ENVI, and/or Google Earth Engine. - Experience with cloud-based geospatial workflows (AWS, Google Cloud, or Azure) and version control practices (Git/GitLab/GitHub). - Strong written and verbal communication skills with demonstrated ability to present complex technical findings to both technical and non-technical audiences. Desired / Preferred Qualifications: - Active Top Secret/SCI clearance — candidates who already hold an active TS/SCI will be given strong preference and can expect an accelerated onboarding timeline. - Experience supporting DoD, Intelligence Community, or national security remote sensing programs (NRO, NGA, AFRL, ARO, or equivalent). - Familiarity with hyperspectral sensing platforms (e.g., AVIRIS, PRISMA, orbital hyperspectral systems) and hyperspectral analytics pipelines including mineral characterization and vegetation health assessment. - Experience applying deep learning frameworks (PyTorch, TensorFlow, Hugging Face) to geospatial or computer vision tasks, including fine-tuning foundation models or geospatial FMs (e.g., Prithvi, SatMAE, Clay). - Background in SAR processing, LiDAR analysis, or multi-modal sensor fusion for environmental or intelligence applications. - Experience with automated testing frameworks, CI/CD pipelines, and MLOps practices for geospatial AI/ML systems. - Track record of peer-reviewed publication, conference presentations (e.g., IGARSS, AGU, SPIE), or technical reports in remote sensing or geospatial AI. - Demonstrated experience in a lead or senior individual contributor role, including mentorship of junior technical staff and coordination across multi-disciplinary teams. - Familiarity with GEOINT tradecraft, NSDI standards, or DoD geospatial data standards (NTM, NITF, STANAG imagery formats). Global Comp $115,000 - $200,000 This represents the typical compensation range for this position based on experience, location and other factors. Closing Statement Riverside Research Institute is a not-for-profit, technology-oriented defense company, where service to our customers and support of our staff is our overall mission. Riverside is an affirmative action-equal opportunity employer and complies with all applicable federal, state, and local laws regarding recruitment and hiring. Riverside offers comprehensive compensation and benefit packages to our employees. Riverside bases its employment decisions solely on technical experience, qualifications and other job-related criteria related to our organizational purpose as a not-for-profit company, and without regard to race, color, religion, age, sex marital status, sexual orientation, national origin, physical or mental disability, veteran’s status or any other status legally protected by applicable federal, state, and local law.

• Prepare and review engineering designs and technical specifications • Perform technical analysis and validation of designs • Support coordination between engineering disciplines • Participate in technical meetings and define design solutions • Ensure compliance with applicable technical standards