Senior Software Engineer - Applied AI
Leonardo DRSAbout the role
Job ID: 114693
DRS RADA Technologies, a subsidiary of Leonardo DRS, is focused on proprietary radar solutions and legacy avionics systems supporting the defense industry globally. The company is a global pioneer of AESA tactical radars for active military protection, counter-drone applications, critical infrastructure protection, and border surveillance.
Job Summary
DRS RADA Technologies in Germantown, MD, is hiring a Senior Software Engineer-Applied AI. This position is full time and on-site.
We are a global pioneer in AESA tactical radar, as a Senior Software Engineer-Applied AI, you'll build the tools, backend services, and internal applications that bring AI/ML into our software development and business workflows. This is a hands-on engineering role: you'll ship LLM integrations, retrieval and summarization pipelines, workflow automation, and classification tooling on a Linux-based platform, working in Python alongside engineers building Rust microservices and TypeScript UIs.
You'll partner with technical leads and domain experts to turn AI/ML requirements into maintainable, production-grade software, owning the engineering that takes models from prototype to production. As a senior member of the team, you'll also mentor engineers and set the bar on design, code quality, and engineering practices.
Job Responsibilities
- Design, build, and maintain internal tools, backend services, and automation workflows in Python on a Linux platform
- Develop AI/ML-enabled features: document search, summarization, extraction, retrieval-based workflows, and intelligent automation
- Integrate LLMs, APIs, and internal/external services; define service interfaces and data contracts across Python, Rust, and TypeScript
- Support the ML lifecycle (dataset preparation, labeling, training/evaluation automation, and model integration) in partnership with technical leads and domain experts
- Write testable, production-quality code and own deployment, logging, troubleshooting, and documentation in Linux environments
- Mentor engineers and provide technical leadership on design and sound engineering practices
Qualifications
- Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related field, or equivalent practical experience
- 5+ years of professional software development experience
- Strong Python proficiency and experience building software in Linux environments
- Experience building backend services, internal tools, automation, or APIs, working with both structured and unstructured data
- Hands-on experience with AI/ML-enabled applications (e.g., document search, summarization, extraction, prompt-based workflows, model evaluation/integration, or classification pipelines)
- Familiarity with modern engineering practices: version control, testing, debugging, and code review
- Strong problem-solving skills and effective collaboration across backend, platform, and UI teams and with domain experts
Preferred Qualifications
- RAG pipelines, embeddings, vector search, or document retrieval workflows
- Ollama, open-source LLMs, or private/local model deployment
- LangChain, LlamaIndex, or similar orchestration frameworks
- FastAPI, Flask, or similar backend frameworks; microservice and service-integration patterns
- Docker, CI/CD, logging, and observability in Linux environments
- Model evaluation or classification work using structured, image, time-series, or sensor-derived datasets
U.S. Citizenship required. This position requires an active DOD security clearance or the ability to obtain such clearance within a reasonable time after commencement of employment.
The salary range for this position is $107,089.00-$155,000.00. This range reflects the good faith estimate of pay the employer is willing to offer at the time of posting. Several factors can influence the pay scale, including but not limited to: Federal contract labor categories and contract wage rates, collective bargaining agreements, geographic location, business considerations, scope, and responsibilities of the position, local or other applicable market conditions, and internal equity. Other factors include the candidate’s qualifications such as prior work experience, specific skills and competencies, education/training, and certifications. In addition to base pay, employees may be eligi
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