Mid-Level AI Software Developer

If you are an experienced, collaborative self-starter with AI development experience, D2 is the place for you.

Here, you can make your career your own by embracing autonomy, seizing opportunity, and being trusted to deliver your best every day.

There is not a challenge we can’t turn into an opportunity.

Our work depends on a TS/SCI level cleared AI Developer joining our team to support our Intelligence customer in Springfield, VA.

What you get to do every day:

• Integrate multiple data streams into customer system
• Complete Cloud platform migrations (between currently existing and available platforms)
• Develop AI features for existing Ontology-based software applications
• Creates sustainable software applications – work is estimated accurately, branching strategies are efficient, code repos are maintained, etc.
• Work as a member of an agile scrum team and participates in regular agile ceremonies applying scrum methodologies – daily stand up, planning, sprint reviews, demos, retrospectives
• Implement requirements from the product backlog
• Assist in writing backlog requirements/user stories
• Utilize a modern DevSecOps approach in building software applications
• Develop and modify applications, software, services, utilities, interfaces, and IT systems that support systems and analysts

Required skills:

• 5+ years of experience
• Bachelor’s degree in Computer Science, computer engineering, systems engineering, or any related field/major, or 3 additional years of experience in information technology.
• Professional software development experience designing, developing, and maintaining secure, scalable, and mission-focused applications
• Professional programming experience with Pyton, Java, and Scala
• Experience developing and integrating RESTful APIs, Git-based workflows, automated unit/integration/system testing, CI/CD pipelines, and modern software delivery practices
• Hands-on experience with Docker/containerization, microservice architectures, Helm, and development container environments
• Exposure to Generative AI technologies, including Retrieval-Augmented Generation (RAG), Large Language Models (LLMs) and LLM-enabled workflows