AI-Native Software Engineer - JobID-0024

Innovative Defense Technologies•Arlington, VA

21h•Onsite

About The Position

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 DoW 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 US Navy. 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.

Requirements

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 GitHub 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 AI-specific security risks as they pertain to a full SDLC
Strong problem-solving skills with the ability to define requirements, scope projects, and deliver solutions independently
Strong communication skills — ability to collaborate and explain complex concepts to diverse audiences, and synthesize details into actionable recommendations and implementations
Cross-functional collaboration — builds strong relationships across engineering, security, compliance, etc.

Nice To Haves

Experience building AI-augmented developer tooling
Familiarity with LLM orchestration frameworks (LangChain, LangGraph, Semantic Kernel, etc.)
Experience integrating AI capabilities into DevSecOps pipelines
Experience deploying or operating self-hosted LLMs in secure environments
Proficiency in containerization (Docker, Podman, etc.) and orchestration frameworks (Swarm, Kubernetes, etc.)
Development, system integration, and test experience with complex DoW systems
Experience supporting and working with cross-functional teams in a dynamic environment
Familiarity with US Navy and US Army tactical C2 or sensors such as Aegis, CEC, CAC2S, IBCS, SPY-1, etc. system design is desired
Experience with creating and configuring Virtual Machines (VMware, VirtualBox, etc.)
Problem-solving skills with the ability to navigate ambiguous situations
Excellence in technical communication with peers and non-technical cohorts
Ability to work closely with Program Managers and Chief Engineers to document, manage and communicate systems and software requirements
Attention to detail
Initiative, creativity, reliability, teamwork
Strong organization and planning skills
Solid analytical abilities, coupled with a strong sense of ownership, urgency and drive

Responsibilities

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 DoW 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.