AI-Native Software Engineer
Listed on 2026-05-25
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Software Development
AI Engineer, Machine Learning/ ML Engineer
AI-Native Software Engineer
- -0024
Department: Engineering
Employment Type: Full Time
Location: Arlington, VA
Compensation: $114,000 - $231,000 / year
DescriptionAbout The Role: Innovative Defense Technologies (IDT), a leading defense technology company, is seeking an AI-Native Software Engineer to be part of our Warfare Systems team and based out of our Arlington, VA location. They will develop software in an AI-augmented engineering environment where generative AI tools are used throughout the software lifecycle—including requirements analysis, architecture design, code generation, test creation, debugging, documentation, and system analysis.
This engineer will work within multidisciplinary teams to accelerate delivery, enhance reliability, and operationalize autonomous and intelligent behaviors across complex DoD systems and is ideal for engineers who actively experiment with new AI tools and enjoy discovering faster and more effective ways to build software.
The Warfare Systems business area is one of six mission‑critical business units within the IDT organization and is directly responsible for building, testing, and deploying the Navy’s next generation of tactical warfare and weapons systems. As the nation enters the “technology‑first” era of warfare, the Warfare Systems group will be responsible for enabling and accelerating the mission‑critical tactical capability that is delivered to the warfighter.
The Warfare System AI‑Native Software Engineer will work with our team of software and systems engineers, building tactically relevant and technically innovative solutions to ensure the highest impact on the U.S. Navy.
Clearance & Location Requirements:
- All applicants must currently possess an active Secret U.S. Security Clearance.
- This is an on‑site position. Requiring at least 3 days in office, based out of our Arlington, VA location.
- Use generative AI tools (LLM copilots, autonomous coding agents, AI test generators) as a core part of daily software engineering workflows
- Demonstrate and share AI‑enabled engineering techniques that improve team productivity and software quality
- Help define and evolve AI‑augmented engineering standards, patterns, and best practices
- Prototype and evaluate emerging AI developer tooling (agent frameworks, code copilots, automated testing agents)
- Mentor engineering teams on effective use of generative AI in development workflows
- Integrate AI Components into Complex DoD Software Environments
- Integrate AI models and services into mission‑critical software systems
- Develop Intelligent Data Processing and NLP Pipelines
- Deliver AI‑Enabled Dashboards, Interfaces, and Insights
- Help identify areas of the software lifecycle that can be accelerated through generative AI and automation
Required:
- Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field, or equivalent full‑time professional experience
- 5‑7 years of full‑time professional experience
- Ability to travel up to 10% of the time, as needed
- Demonstrated curiosity and experimentation with emerging AI technologies and engineering practices
- Daily use of generative AI coding tools such as Git Hub Copilot, Cursor, Codeium, ChatGPT, Claude, or similar systems
- Experience using LLMs for code generation, debugging, test generation, and documentation automation
- Familiarity with agent‑based development workflows and AI‑assisted engineering environments
- Experience designing prompt workflows or system prompts to improve developer productivity
- Ability to critically evaluate AI‑generated code for correctness, security, and performance
- Strong understanding of AI concepts and practical deployment patterns
- Demonstrated ability to scope requirements for engineering solutions that meet business challenges using AI with measurable outcomes
- Experience in engineering solutions that integrate AI models into production workflows to improve user experience and productivity
- Understanding of security and compliance considerations when implementing AI solutions, especially in sensitive or classified environments, to support multiple deployment environments
- Understanding of secure software development practices and…
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