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Designs, implements, debugs, and leads development of RF signal processing software (detectors, demodulators, protocol processors). Develops algorithms (FFT, filtering, beamforming), integrates software into systems, writes and reviews documentation, executes tests, troubleshoots hardware/software issues, and ensures software quality and process improvement across teams.

The Cloud Engineer will design, maintain, and support cloud infrastructure, collaborate with architects and engineers, and implement cloud solutions while ensuring compliance with security requirements and best practices.

The MD-Systems Administrator 3 provides IT systems support, troubleshooting, and maintenance, managing operations, configurations, and user assistance, focusing on UNIX and Windows systems and Cisco hardware.

Provide hands-on implementation, troubleshooting, maintenance and day-to-day operations for servers, storage, network and mobile devices. Deliver Tier I and Tier II support, escalate and communicate status, configure UNIX and Windows OS, install system software, manage Cisco routers/switches, perform capacity planning, and resolve complex server hardware and software integration issues within an SOA environment.

Design, deploy, triage, and maintain production NoSQL databases (Elasticsearch, Redis) on Kubernetes platforms, support GitOps adoption, harden databases to NIST 800-53, collaborate with systems, security, and dev teams, and contribute to monitoring, documentation, and Agile processes.

Design and execute manual and automated test strategies and cases; automate tests with Selenium WebDriver; perform functional, regression, integration, and API testing; report and track defects; participate in Agile ceremonies, system design, risk assessments, and CI workflows; gather testing metrics and improve testing processes.

Lead design, development, and deployment of production AI/ML solutions. Collaborate with multidisciplinary teams to build analytics platforms using statistical methods, graph analytics, entity resolution, and LLMs. Work with diverse data types and integrate AI with DevSecOps, data engineering, and observability for mission-critical defense/intelligence applications.

Design and implement distributed backend microservices, APIs, and cloud-native platforms to support enterprise AI operations. Collaborate with multidisciplinary teams to build, deploy, and maintain analytics and AI/ML solutions using event-driven architectures and Kubernetes-native practices. Integrate DevSecOps, data engineering, observability, and cybersecurity for mission-focused outcomes.

Lead design, development, and deployment of advanced analytics and AI/ML solutions. Collaborate with multidisciplinary teams to build production-ready algorithms using statistical analysis, graph analytics, entity resolution, explainable AI, and geospatial and multimodal data. Integrate AI with DevSecOps, data engineering, platform engineering, and observability to deliver mission-focused outcomes.

Design, build, and productionize AI and agentic AI systems for mission environments. Collaborate with cross-functional teams to deliver scalable ML/LLM solutions, including LLMOps, RAG, Kubernetes deployments, GPU-optimized inference, and integrations with DevSecOps and observability tooling.