Jobs at Vantor

The Cybersecurity Engineer secures space-sensing systems supporting defense and national security missions. Responsibilities include analyzing system performance, identifying vulnerabilities, supporting Risk Management Framework activities, conducting mission-based cyber risk assessments, developing threat scenarios for cyber test events, evaluating cybersecurity architectures and network diagrams, and integrating security throughout the system lifecycle. The role requires collaboration with engineers, operators, and mission stakeholders.

Develops and executes integration plans for space and ground systems supporting Space Force environmental monitoring capabilities. Leads integration across system-of-systems, system, segment, and element levels; researches requirements, technologies, and threats; and applies integration methodologies to remote sensing systems. The role also evaluates technical performance, schedules, costs, risks, contractor data, requirements, interfaces, and verification activities for satellite programs.

Lead project execution for resilient Missile Warning and remote-sensing capabilities supporting the U.S. Space Force. Coordinate technical teams, stakeholders, testing, analysis, evaluation, validation, and verification activities. Manage cost, schedule, performance, and programmatic risks while aligning requirements and driving mitigation. The role requires DoD acquisition experience, cross-functional communication, and regular onsite work two to three days per week or more as needed.

Lead development and management of technical requirements, ICDs, MBSE products, and integration/test plans for space sensing systems. Provide technical guidance to program leadership, perform systems engineering and program management activities, analyze issues, produce technical reports, and coordinate changes across large stakeholder groups to support acquisition and development.

Lead test, evaluation, verification, and validation of missile warning and space-based remote sensing systems. Plan and execute DT&E, develop TEMPs/STPs/RVPs/RVRs, perform data analysis and test reporting, conduct system-of-systems integration tests, facilitate ITTs/DRBs/MIPRBs, decompose requirements, define SUTs, establish acceptance criteria, and collaborate with government clients, FFRDCs, and prime contractors.

Provide spectrum management expertise for Space Force programs: prepare frequency use plans and certifications (DD1494, RFA, ITU), coordinate with SV/LV/ground teams, develop radio network designs and supportability strategies, and ensure compliance with DoD/DAF/NTIA policies. Serve as technical authority, resolve RF issues, and support AFSMO/NTIA submissions.

Lead systems engineering for space sensing and ground systems: test, analyze, verify, and validate missile warning and remote sensing systems; author requirements, technical specifications, ICDs, integration and test plans; coordinate with clients and teams; support acquisition and deploy resilient space and ground architectures.

Develop and maintain scalable Java and Spring Boot REST services, APIs, and microservices for mission-critical geospatial systems. Support containerization, orchestration, CI/CD, DevOps automation, testing, infrastructure deployment, data platforms, and third-party integrations. Contribute to architecture, performance optimization, troubleshooting, documentation, stakeholder demos, and Agile delivery. The role requires onsite work in Herndon, Virginia and collaboration on national security missions.

Leads development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Responsibilities include feature engineering, forecasting, anomaly detection, data integration, ETL, visualization, algorithm evaluation, simulation, dataset creation, and stakeholder communication. The role also contributes to mission-focused software applications, APIs, data pipelines, documentation, code reviews, and agile development while requiring an active Top Secret or CBP/DHS suitability clearance.

Supports AI engineering initiatives at Vantor, contributing to spatial intelligence solutions and helping develop technologies that enable customers to understand current and future conditions. The posting provides limited role-specific responsibilities but emphasizes problem-solving, innovation, collaboration, and mission-focused work. Applicants must qualify as a U.S. Person under applicable export control and ITAR requirements.

Lead the development of statistical and machine learning models for time-series and geospatial data. Build analytic solutions, datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and reports. Evaluate algorithm performance, optimize classifiers, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders to deliver reliable mission-focused software and data capabilities.

Lead and contribute to the design, integration, deployment, and sustainment of mission-focused systems. Translate stakeholder needs into technical requirements, architectures, interface definitions, deployment patterns, and operational processes. Partner with software engineers and data scientists to integrate applications, data pipelines, infrastructure, and external systems. Support testing, verification, troubleshooting, operational readiness, documentation, and reliability improvements for secure, scalable, data-intensive systems.

Develops statistical and machine learning models for kinematic behavior detection using live, historical, time-series, and geospatial data. Responsibilities include data integration, ETL, feature engineering, forecasting, anomaly detection, algorithm evaluation, simulation, visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to mission-focused software applications, APIs, data workflows, code reviews, troubleshooting, and agile development in a remote-first environment.

Lead statistical and machine learning model development for time-series and geospatial data supporting the FALCON mission. Responsibilities include feature engineering, forecasting, anomaly detection, ETL, dataset creation, algorithm evaluation, simulation, data visualization, reporting, documentation, and stakeholder collaboration. The role also contributes to software applications, APIs, data pipelines, code reviews, troubleshooting, and iterative agile development.

Lead development of statistical and machine learning models for time-series, geospatial, kinematic, and radar data. Build analytic solutions, training datasets, ETL workflows, forecasting and anomaly-detection models, simulations, visualizations, and performance metrics. Integrate multi-source sensor data, enhance algorithms, document processes, and collaborate with engineers, analysts, mission partners, and stakeholders in an agile environment.

Develops and executes integration plans for space and ground systems supporting military remote sensing missions. The role evaluates and validates system performance, mitigates integration risks, manages configuration changes, and supports DoD acquisition, sustainment, logistics planning, and lifecycle documentation. Responsibilities span system-of-systems, system, segment, and element levels while coordinating with engineers, analysts, logisticians, and financial managers.

Leads Vantor’s AI-assisted software engineering strategy and transformation. Designs and prototypes agentic workflows for coding, testing, documentation, code review, and automation; evaluates tools; establishes secure governance; runs pilots; builds adoption networks; measures productivity, quality, risk, and business value; and translates evidence into executive recommendations, roadmaps, and scalable operating patterns.

Design, develop, and productionize multimodal AI systems (VLMs, reasoning models, LLMs) for geospatial data. Build end-to-end ML pipelines, experimentation frameworks, synthetic datasets, and scalable inference on cloud infrastructure while collaborating with research, engineering, and product teams.

Design, develop, and productionize multimodal AI systems (VLMs, LLMs, reasoning models) and end-to-end ML pipelines for geospatial data. Build training/experiment frameworks, synthetic datasets, scalable inference, monitoring, and collaborate with research, engineering, and product teams to deliver Earth intelligence solutions.