Data & AI Engineer (Agentic Systems)

Defense Unicorns; Virginia; On-site; USD 149,000 - 201,000; Full time

Benefits offered by this job

Medical/Dental/Vision

Premiums are 100% Company Paid

Health Savings Account

Life Insurance

Disability Insurance

401k Retirement Plan

Company Stock Options

Home Office Budget

Full-time Flexible Time Off

Paid Parental Leave

Reimbursement for trainings/subs

Conferences (travel, lodging, fees)

Job summary

Defense Unicorns in Virginia is seeking an experienced software engineer to design, build, and maintain agentic AI applications that integrate LLMs, tools, APIs, and enterprise data for mission workflows. The role embeds with a government team and requires on-site presence in Springfield, VA roughly 2–3 days per week.

You will implement agent orchestration, RAG pipelines, and backend services in Python, participate in CI/CD, and ensure testing, monitoring, and reliability.

Qualifications

• 3–5 years of software engineering experience or equivalent.
• Hands-on experience building agentic AI applications and multi-step workflows.
• Strong Python proficiency and backend software development
• Experience integrating LLMs via APIs/SDKs
• Experience building REST APIs and integrating external services
• Understanding of agent workflows, state management and error handling
• Git, testing, debugging, and modern DevOps practices
• Cloud-native or containerized environments and collaboration with platform teams
• Ability to work independently and translate mission needs into working software
• Active Top Secret clearance with SCI eligibility required

Responsibilities

• Design, build, and maintain agentic AI applications integrating LLMs, tools, APIs, and enterprise data.
• Develop AI agents that execute multi-step tasks and coordinate actions across systems.
• Implement agent orchestration, tool calling, and workflow state management with robust error handling.
• Build and integrate RAG pipelines, semantic search, embeddings, and vector retrieval.
• Create backend services and APIs using Python and modern software practices.
• Integrate agentic capabilities into existing apps, CI/CD workflows, and enterprise platforms.
• Establish testing, monitoring, and reliability practices for AI agents and components.
• Collaborate with data and platform engineers to ensure reliable data access and deployment on Kubernetes/OpenShift.
• Remediate end-to-end integration challenges with government engineers and partners
• Produce reusable components and documentation for scalable implementations

Skills

Software engineering

Agentic AI

Python

APIs REST

Git

Kubernetes/OpenShift

CI/CD

Cloud-native

Troubleshooting

Clearance

Tools

Kubernetes

OpenShift

CI/CD

LangGraph

LangChain

CrewAI

AutoGen

MCP

Vector databases

Job description

Defense Unicorns is building agentic AI capabilities that can be used for mission applications in secure, classified environments. This role embeds with a government team to help turn reliable LLM-powered systems into repeatable, operational software patterns. Expect practical impact across the full stack, from agent workflows and retrieval pipelines to deployment in Kubernetes/OpenShift and troubleshooting real integrations.

Responsibilities

• Design, build, and maintain agentic AI applications that integrate LLMs, tools, APIs, and enterprise data to support mission workflows.
• Develop AI agents that can 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.
• Create 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 spanning agent behavior, tool execution, APIs, data access, application services, and infrastructure.
• Partner directly with government engineers and commercial technology partners to resolve integration challenges and remove blockers to mission delivery.
• Produce documentation, reusable components, and operational standards so successful implementation patterns can be repeated.
• Operate effectively in a fast-moving, ambiguous environment where technologies, security requirements, and mission priorities evolve.

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 Python proficiency and backend software development experience.
• 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 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 required.

Technologies

• Python, LLMs, REST APIs, Git
• Kubernetes, OpenShift, CI/CD
• RAG, semantic search, embeddings, vector-based retrieval, vector databases
• Helm, Kustomize, Terraform, Pulumi, GitOps
• CNCF projects
• LangGraph, LangChain, CrewAI, AutoGen, Model Context Protocol (MCP)
• Knowledge graphs
• Open-source products and packages

Benefits

• Medical/Dental/Vision
• Premiums are 100% Company Paid
• Health Savings Account
• Life Insurance
• Disability Insurance
• 401k Retirement Plan
• Company Stock Options
• Home Office Budget
• Full-time Flexible Time Off (FTO) plus all Federal Holidays, one week for Thanksgiving, and two weeks for Christmas and New Year's
• Paid Parental Leave
• Reimbursement for approved trainings/subscriptions
• Conferences (travel, lodging, and fees)

Location and Onsite Requirement

Virginia (onsite). Local to the National Capital Region and able to support onsite work at a government facility in Springfield, VA as mission needs require: approximately 2–3 days per week onsite, with additional onsite presence as mission needs increase.

Mission Focus

Enable trusted data access where AI needs it, and establish repeatable, secure data patterns to move from experimentation to operational capability.

Compensation: USD 148,750 - 201,250 per year.