Applied AI Engineer

STR’s Intelligence Division researches, develops, and transitions advanced analytics and machine-learning solutions for challenging national-security problems. Our team includes engineers and researchers with advanced backgrounds in engineering, computer science, mathematics, and data science who apply deep technical expertise and creativity to mission-critical challenges.

Our work spans data analysis, deep learning, and statistical methods across networking, communications, social media, text, time series, geospatial, and imagery data. We develop capabilities under constraints not typically encountered in commercial environments. U.S. Government analysts use our tools and technologies to extract, enrich, and act on intelligence information worldwide.

As an Applied AI Engineer, you will develop, integrate, test, and maintain software that supports advanced analytics, machine learning, and intelligence workflows, with a focus on RF sensing, waveform generation, communications, and networking systems. You will work with a multidisciplinary team to transform defined requirements and technical designs into reliable, maintainable, and mission-relevant software capabilities.

You will contribute across the development lifecycle, including implementation, debugging, testing, documentation, integration, and operational support. This role provides opportunities to grow technical depth and independently own well-defined components within larger systems.

This is a technical individual-contributor role. You will independently execute well-scoped technical tasks, communicate progress and blockers, and seek guidance when requirements, interfaces, or technical decisions require clarification.

• → Develop software: Implement, test, debug, and maintain software components, services, APIs, data-processing capabilities, tools, or user interfaces supporting AI/ML, RF sensing, communications, and networking workflows
• →Deliver assigned capabilities: Implement well-scoped features, modules, integrations, and fixes from defined requirements and technical designs. Contribute to AI/ML, RF sensing, waveform generation/adaptation, communications, and networking capabilities within larger systems
• →Support integration and test: Participate in unit, integration, system, and regression testing; troubleshoot issues and support demonstrations and releases. Support integration of software with RF/sensor data sources, AI/ML models, communications services, Open RAN components, waveform generation/adaptation, and edge or on-premises compute environments
• →Apply engineering practices: Use version control, code review, automated testing, issue tracking, documentation, and secure coding practices to develop reliable, maintainable software
• →Collaborate across the team: Work with software engineers, systems engineers, RF/communications researchers, DevSecOps personnel, and other stakeholders to clarify requirements, resolve technical issues, and communicate progress, findings, and blockers
• →Improve existing systems: Identify and implement improvements to reliability, performance, maintainability, usability, and testability. Contribute to AI/ML-enabled RF sensing and communications capabilities
• →Build technical depth: Learn team technologies, domain context, development workflows, and deployment environments while taking increasing ownership of assigned work. Build familiarity with AI/ML, RF sensing, Open RAN, edge AI, and high-throughput or latency-sensitive communications workflows as applicable

• Education and experience: MS, or BS with 2 years of relevant experience in computer science, software engineering, computer engineering, or a related technical discipline
• Clearance eligibility: Ability to obtain and maintain a Secret or Top Secret security clearance, for which U.S citizenship is needed by the U.S government
• Programming foundation: Proficiency in at least one programming language, such as Python, C++, Java, Go, or similar languages
• AI/ML and communications experience: Experience applying AI/ML techniques and tools to solve technical problems involving sensor, time-series, RF, communications, or other non-textual data. Experience with RF signal processing, wireless communications, 5G/6G RAN, O-RAN/AI-RAN, waveform generation/adaptation, or edge AI is strongly preferred
• Software development experience: Experience developing, testing, debugging, and maintaining software through coursework, internships, research, professional work, or personal projects. Ability to implement defined designs, troubleshoot technical issues, and contribute to integrated software systems
• Engineering fundamentals: Familiarity with object-oriented design, data structures, algorithms, software design patterns, and version-control systems such as Git
• Quality mindset: Familiarity with unit testing, debugging, documentation, code review, CI/CD, containers, and secure software-development practices
• Collaboration and communication: Ability to work effectively on a technical team; communicate progress, technical findings, and blockers clearly; and seek guidance when technical requirements or decisions are unclear

• Active Secret or Top Secret security clearance
• RF and wireless systems: Experience with digital signal processing, software-defined radios, RF sensing, wireless communications, or PHY/MAC processing.
• AI-RAN and edge deployment: Familiarity with 5G/6G, Open RAN, or AI-RAN architectures and deployment of AI/ML models to edge, GPU-enabled, resource-constrained, or hardware-accelerated compute platforms.
• Real-time communications software: Experience developing or testing high-throughput, latency-sensitive software for RF sensing, PHY, MAC, scheduling, radio-resource management, or related functions.
• Containers and deployment: Familiarity with Docker, CI/CD pipelines, Linux deployment environments, cloud services, Kubernetes, monitoring, logging, or infrastructure automation.
• Web and API development: Experience developing REST APIs, backend services, web applications, dashboards, visualization tools, or data-processing services.
• Data and decentralized systems: Familiarity with message queues, stream processing, distributed computing, microservices, time-series data, or real-time analytics pipelines.
• Modern development tools: Experience using LLM-enabled development tools, such as Cursor or Codex, in a secure and effective engineering workflow
• Mission experience: Experience supporting DoW, IC, or other U.S. Government customers through internships, research, employment, or related programs

Pay Information
Full-Time Salary Range: $120,000 - $150,000

The salary range listed is based on external market data. Offers are based on factors, such as but not limited to, the candidate’s experience, education, training, key skills/critical skills, security clearances, and prevailing market and business conditions.