Agentic AI Engineer - LLM Workflows & Orchestration

defenseunicorns; Springfield (VA); On-site; USD 140,000 - 190,000; Full time

Job summary

Defense Unicorns seeks an Applied AI Engineer to embed with a government team and its technology partners to design, build, and integrate agentic AI capabilities across LLM integration, tool calls, and enterprise data. You will work in secure environments, delivering reliable software for mission-critical workflows.

You will collaborate with data and platform engineers, deploy in Kubernetes/OpenShift, and contribute to reusable components, documentation, and operational standards while

Qualifications

• 3–5 years of software engineering experience.
• Hands-on experience building agentic AI applications, including AI agents, LLM tool calling, multi-step workflows, or agent orchestration.
• Strong proficiency with Python and backend software development.
• Experience integrating LLMs into applications using APIs, SDKs, or comparable technologies.
• Experience building and integrating REST APIs and connecting applications with external services or data sources.
• Understanding of agent workflows, tool execution, state management, and error handling.
• Experience with Git, testing, debugging, and modern software development practices.
• Experience working in cloud-native or containerized environments and collaborating with platform engineering teams.
• Ability to troubleshoot application and integration issues across APIs, data services, infrastructure, and AI components.
• Ability to work independently, rapidly learn new technologies, and translate ambiguous mission needs into working software.
• GEOINT experience is preferred, not required.
• Relevant agentic AI experience may be demonstrated through professional work, internships, research, open-source contributions, or independent projects.

Responsibilities

• Design, build, and maintain agentic AI applications that integrate LLMs, tools, APIs, and enterprise data to support mission workflows.
• Develop AI agents capable of executing multi-step tasks, interacting with external services, and coordinating actions across existing systems.
• Implement agent orchestration, tool calling, workflow state management, error handling, and appropriate human oversight.
• Build and integrate RAG pipelines, semantic search, embeddings, and vector-based retrieval to provide relevant context for AI applications.
• Develop backend services and APIs using Python and modern software engineering practices.
• Integrate agentic AI capabilities into existing applications, software delivery workflows, and enterprise platforms.
• Establish testing, evaluation, monitoring, and reliability practices for AI agents and LLM-powered applications.
• Collaborate with data engineers to ensure agents can access reliable, relevant, and appropriately governed enterprise data.
• Work with platform engineers to deploy and operate AI applications within Kubernetes/OpenShift environments and integrate them into CI/CD workflows.
• Troubleshoot end-to-end issues involving agent behavior, tool execution, APIs, data access, application services, and infrastructure.
• Work directly with government engineers and commercial technology partners to resolve integration challenges and remove blockers to mission delivery.
• Develop documentation, reusable components, and operational standards that make successful AI implementation patterns repeatable.
• Operate effectively in a fast-moving, ambiguous environment where technologies, security requirements, and mission priorities continue to evolve.
• Local to the National Capital Region and able to support onsite work at a government facility in Springfield, VA as mission needs increase.

Skills

Python programming

Backend software development

Independent work

Problem solving

Tools

REST APIs

Git

CI/CD

Docker/Kubernetes

Job description

Defense Unicorns seeks an Applied AI Engineer to embed with a government team and its technology partners to design, build, and integrate agentic AI capabilities across LLM integration, tool calls, and enterprise data. You will work in secure environments, delivering reliable software for mission-critical workflows.

You will collaborate with data and platform engineers, deploy in Kubernetes/OpenShift, and contribute to reusable components, documentation, and operational standards while