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Required Frontend Developer
As part of your role you will have the opportunity to:
Design and implement client-side features
Be fully involved from the kick-off phase with Product Management and UI/UX, all the way to production deployment
Work closely with other teams in the R&D in an agile environment
Direct customer impact, design, develop and deploy in short cycles.

We are looking for a highly skilled RF Test Automation Developer to join our R&D Integration Automation team.

This role is focused on designing, developing, and maintaining advanced automation solutions across unit, integration, system, and end-to-end testing levels.

The ideal candidate is a hands-on developer with strong expertise in Python and Pytest, experienced in building and executing automated tests, and comfortable working with modern CI/CD pipelines and automation tools.

The Senior Developer will act as a technical mentor and key contributor, ensuring best practices are followed and test automation is seamlessly embedded into the development lifecycle.

Knowledge of RF systems is a strong plus.

Key Responsibilities:
Develop and maintain automated RF test development tools using Python and other relevant programming languages.
Configure, calibrate, and operate RF test equipment such as Vector Signal Generators (VSGs), Spectrum Analyzers (SAs), and related instruments.
Create and validate RF test setups for performance validation, debug, and system characterization.
Analyze test results, generate comprehensive reports, and present findings to cross-functional teams.
Collaborate with hardware and software engineers to integrate automated RF testing into the product development cycle.
Stay current with emerging RF technologies and testing methodologies, proposing and implementing improvements to existing test processes.
Contribute to the development of RF testing strategies aligned with R&D goals and product roadmaps.
Research and introduce innovative RF automation tools, frameworks, and workflows aligned with R&D goals.

Required DevOps Engineer
As part of the role you will have the opportunity to:
Be a member of a strong team responsible for all DevOps aspects in the company: Cloud infrastructure, CI/CD, Monitoring, DataOps, SecOps and cost management
Architect, automate and manage cloud infrastructure (Azure & AWS)
Implement SecOps best practices in all infrastructure and processes
Integrate visibility and alerting capabilities into infrastructure and processes
Improve and automate CI/CD pipelines.

Required Backend Software Engineer
As part of the role you will have the opportunity to:
Research, design, maintain and develop core data infrastructure components
Analyze and optimize system performance, scalability, reliability, and data quality across a rich technology stack (Apache Kafka, Airflow, Storm, SQL/NoSQL databases)
Architect, design, and implement robust, performant distributed data systems (streaming and batch processing).
Collaborate with cross-functional teams to integrate data pipelines with AI/ML workflows and production monitoring systems.
Work in a fast-paced startup environment, managing multiple priorities while maintaining high code quality and operational excellence.

We are looking for a highly skilled Senior Developer - Python Automation Infrastructure and testing to join our R&D Integration Automation team. This role is focused on designing, developing, and maintaining advanced automation solutions across unit, integration, system, and end-to-end testing levels.
The ideal candidate is a hands-on developer with strong expertise in Python and Pytest, experienced in building and executing automated tests, and comfortable working with modern CI/CD pipelines and automation tools. The Senior Developer will act as a technical mentor and key contributor, ensuring best practices are followed and test automation is seamlessly embedded into the development lifecycle. Knowledge of RF systems is a strong plus.
Key Responsibilities:
Design, implement, and maintain automation frameworks and test scripts using Python and Pytest.
Write unit tests, integration tests, and regression suites to ensure comprehensive test coverage.
Develop and execute system-level and end-to-end automation, including API and UI layers (Selenium preferred).
Contribute to and optimize CI/CD pipelines (Jenkins, Docker, Git) for reliable and scalable test automation.
Collaborate closely with SW developers, RF, QA, and DevOps engineers to embed automated testing into every phase of the product lifecycle.
Perform code reviews, provide technical guidance, and ensure automation code meets high quality and maintainability standards.
Analyze test results, identify root causes of failures, and drive timely resolution in partnership with development teams.
Continuously evaluate and introduce new tools, libraries, and practices to improve automation efficiency.
Support integration activities and ensure smooth interaction between hardware, software, and automation systems.

Required Backend Software Engineer- Platform
As part of the role you will have the opportunity to:
Be part of team responsible for designing and implementing our next generation on-premise component that facilitates communication with our customer's IoT devices - a.k.a the native connector
Help develop & maintain the underlying infrastructure that enables scalable , cost-efficient & secure communication between our cloud-native platform and the Network components & IoT devices that reside on-premise
Research & develop features that allow remote management of components that reside on premise
Help develop & maintain our IoT agent-based embedded software solution that is deployed directly onto the IoT edge devices
Research & develop integration with various external 3rd party solutions in a cloud-to-cloud and cloud-to-on-premise formations using a variety of APIs, including REST, SDKs, and other network protocols
Develop new backend services in micro-service architecture and cloud-native best practices
Guide and mentor team members
Troubleshoot and resolve technical issues, ensuring seamless operation of our services & integrations.

We are seeking a highly skilled Senior Communication PHY Algorithms Engineer.
This senior role is focused on the end-to-end research, design, and implementation of digital receivers for proprietary drone communication signals.
Responsibilities:
Mathematically characterize complex communication and signal detection problems. Analyze and assess design trade-offs based on both performance metrics and implementation complexity.
Develop and maintain simulations using MATLAB and Python.
Design digital receiver modules to be implemented either by FPGA of SW.
Implement features directly in SW or technically lead and verify the FPGA implementation efforts of the FPGA engineer.
Accompany the integration process of the feature until its end-to-end operation.

Required Senior Backend Engineer
As part of the role you will have the opportunity to:
Research, design, maintain and develop core data infrastructure components
Analyze and optimize system performance, scalability, reliability, and data quality across a rich technology stack (Apache Kafka, Airflow, Storm, SQL/NoSQL databases)
Architect, design, and implement robust, performant distributed data systems (streaming and batch processing).
Collaborate with cross-functional teams to integrate data pipelines with AI/ML workflows and production monitoring systems.
Mentor and guide junior engineers, defining technical best practices and driving continuous improvements.
Work in a fast-paced startup environment, managing multiple priorities while maintaining high code quality and operational excellence.

The Opportunity We are starting a new ML/AI organization directly reporting to the CTO, to pioneer next-generation capabilities for our industry-leading defense systems. As a Founding ML-Engineering Lead, you will be the technical cornerstone of this initiative. This is a high-impact role designed for a practitioner who seeks total technical ownership of the machine learning lifecycle. You will be responsible for taking novel AI projects from initial concept through data collection, design, implementation, and evaluation, all the way to deployment.

The Technical Challenge Our ML initiatives span a diverse technical landscape. You will lead projects that range from field-oriented applications, where high accuracy and reliability are paramount, to research-oriented tools and agentic workflows designed to enhance our R&D capabilities and accelerate complex data analysis. Working in deep collaboration with our R&D teams, you will leverage unique, proprietary data to solve problems at the forefront of the counter-drone industry.
What You Will Do:
End-to-End Ownership: Lead the full technical execution of ML projects, ensuring every stage-from data acquisition to deployment-meets our rigorous standards.
R&D Collaboration: Partner closely with R&D departments to design data collection strategies and integrate ML-based tools and agents into their specialized workflows.
Versatile Implementation: Develop models and intelligent systems for a variety of use cases, ranging from real-time field performance to autonomous research-support tools.
Technical Authority: Act as a founding voice for ML implementation and strategy within the CTOs office.

We are seeking an experienced and visionary Data Scientist to join our dynamic technology organization. The successful candidate will be a part of a team of talented data scientists, driving innovation and delivering business value through advanced machine learning techniques and Generative AI solutions. This role requires a strategic thinker with hands-on expertise in both traditional and cutting-edge data science methodologies, and a passion for continuous learning and development.
Responsibilities:
Gradient boosting techniques (e.g., XGBoost, LightGBM, CatBoost) are used to enhance predictive accuracy and model robustness.
Drive the exploration and integration of Generative AI applications, including Large Language Models (LLMs), to create innovative solutions for our products and services.
Collaborate with cross-functional teams (engineering, product, business) to translate business requirements into actionable data science projects.
Establish best practices for model development, validation, deployment, and monitoring in production environments.
Promote a data-driven culture, encouraging experimentation, sharing of knowledge, and adoption of state-of-the-art technologies.
Communicate project progress, insights, and results to stakeholders at all levels of the organization. Design, implement, and optimize classic machine learning models to solve complex business problems.