Applied AI Engineer – Agentic Systems
About The Position
Defense Unicorns is seeking an Applied AI Engineer to embed with a government team and its technology partners to build an emerging AI-powered engineering ecosystem. The role designs, builds, and integrates agentic AI capabilities that enable models to interact with tools, access enterprise data, execute multi-step workflows, and support mission applications. Work spans LLM integration, agent orchestration, APIs, retrieval-augmented generation (RAG), and connections between AI applications and existing software platforms. This is a hands-on software engineering role focused on building reliable, repeatable agentic capabilities that progress beyond experimentation to working software in secure and classified environments. It is not a traditional AI research or model development role. The engineer will join an evolving architecture, learn unfamiliar systems, work directly with commercial technology partners, and address integration, reliability, performance, and security challenges. The position is listed as Remote - USA, with approximately 2–3 days per week onsite at a government facility in Springfield, Virginia, and additional onsite presence as mission needs increase. Candidates must be local to the National Capital Region. An active Top Secret clearance with SCI eligibility is required.
Requirements
- Approximately 3–5 years of software engineering experience, or equivalent demonstrated technical capability.
- 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.
- Active Top Secret clearance with SCI eligibility.
- Local to the National Capital Region and able to support onsite work in Springfield, Virginia, approximately 2–3 days per week, with additional onsite presence as mission needs increase.
Nice To Haves
- GEOINT experience.
- Experience with agentic AI frameworks such as LangGraph, LangChain, CrewAI, AutoGen, or comparable technologies.
- Experience developing multi-agent systems, autonomous workflows, or AI-enabled software development tools.
- Experience with Model Context Protocol (MCP), function calling, or other tool integration patterns.
- Experience with RAG, embeddings, vector databases, semantic search, or knowledge graphs.
- Relevant agentic AI experience demonstrated through professional work, internships, research, open-source contributions, or independent projects.
Responsibilities
- Design, build, and maintain agentic AI applications integrating LLMs, tools, APIs, and enterprise data to support mission workflows.
- Develop AI agents that execute multi-step tasks, interact with external services, and coordinate 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 in 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.
- Support onsite work at a government facility in Springfield, Virginia, approximately 2–3 days per week and more often as mission needs increase.
Benefits
- Medical, dental, and vision coverage with premiums 100% company paid.
- Health Savings Account.
- Life insurance.
- Disability insurance.
- 401(k) retirement plan.
- Company stock options.
- Home office budget.
- Flexible Time Off (FTO) for all full-time employees.
- Federal holidays, one week off for Thanksgiving, and two weeks off for Christmas and New Year’s.
- Paid parental leave.
- Reimbursement for approved trainings and subscriptions.
- Conference travel, lodging, and fees.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
