Generative AI Engineer (Clearance Required)

InterImage, Inc.; Arlington, Northern (VA, KY); Hybrid; USD 150,000 - 190,000; Full time

Job summary

InterImage, Inc. seeks engineers to take Generative AI concepts from proof of concept to production. You will design, develop, deploy, and continuously improve AI-powered applications for mission-critical customers in Azure cloud environments.

The role emphasizes building with LLMs, RAG systems, and secure cloud-native architectures. Strong Python, API, and DevSecOps experience are required, along with an active Top Secret clearance and collaboration with cross-functional teams.

Qualifications

• Active Top Secret Clearance required.
• 5+ years of software development experience.
• 2+ years developing Generative AI or Machine Learning applications.
• Strong Python development experience.
• Experience with Large Language Models including GPT, Llama, Claude, Mistral, or similar models.
• Experience with prompt engineering and AI workflow development.
• Experience building APIs using FastAPI, Flask, or similar frameworks.
• Experience deploying cloud-native applications in Microsoft Azure.
• Familiarity with containerization technologies including Docker and Kubernetes.
• Experience with Git, CI/CD pipelines, and DevSecOps practices.
• Strong understanding of software architecture and distributed systems.

Responsibilities

• Design and build Generative AI applications using commercial and open-source Large Language Models (LLMs).
• Develop proof-of-concepts that evolve into production-ready software.
• Architect Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise data sources.
• Build intelligent agents and AI workflows capable of reasoning, automation, and decision support.
• Develop REST APIs and backend services supporting AI applications.
• Deploy scalable AI solutions within Microsoft Azure environments.
• Design cloud-native architectures using Azure AI Services, Azure OpenAI, Azure Kubernetes Service (AKS), Azure Functions, and Azure Storage.
• Build CI/CD pipelines supporting rapid AI deployment and model iteration.
• Integrate AI capabilities into existing enterprise applications and mission systems.
• Evaluate emerging AI technologies and rapidly prototype new capabilities.
• Collaborate with software engineers, cloud architects, data scientists, and mission stakeholders to deliver innovative solutions.
• Optimize model performance, latency, scalability, security, and cost.
• Implement responsible AI practices, prompt engineering strategies, guardrails, and model evaluation techniques.

Skills

Top Secret Clearance

5+ years software development

2+ years Gen AI / ML

Python

Prompt engineering

AI workflow development

APIs design

Software architecture

Distributed systems

Git & CI/CD

DevSecOps

Tools

Azure cloud services

Docker

Kubernetes

FastAPI/Flask

Azure OpenAI

LangChain / LangGraph

Vector databases (Pinecone / Milvus / pgvector / Azure AI Search / Chroma)

Terraform / Bicep (IaC)

Azure Storage

AKS

Job description

InterImage is looking for engineers who thrive where innovation meets execution. Our Product Division rapidly transforms emerging technologies into operational capabilities supporting mission-critical customers. This isn't a research-only position. You'll take Generative AI concepts from proof of concept to production, designing, developing, deploying, and continuously improving AI-powered applications that solve real-world operational problems. If you enjoy building with the latest LLMs, experimenting with emerging AI technologies, and deploying secure cloud-native solutions in Azure, we'd like to meet you.

What You'll Do

• Design and build Generative AI applications using commercial and open-source Large Language Models (LLMs).
• Develop proof-of-concepts that evolve into production-ready software.
• Architect Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise data sources.
• Build intelligent agents and AI workflows capable of reasoning, automation, and decision support.
• Develop REST APIs and backend services supporting AI applications.
• Deploy scalable AI solutions within Microsoft Azure environments.
• Design cloud-native architectures using Azure AI Services, Azure OpenAI, Azure Kubernetes Service (AKS), Azure Functions, and Azure Storage.
• Build CI/CD pipelines supporting rapid AI deployment and model iteration.
• Integrate AI capabilities into existing enterprise applications and mission systems.
• Evaluate emerging AI technologies and rapidly prototype new capabilities.
• Collaborate with software engineers, cloud architects, data scientists, and mission stakeholders to deliver innovative solutions.
• Optimize model performance, latency, scalability, security, and cost.
• Implement responsible AI practices, prompt engineering strategies, guardrails, and model evaluation techniques.

• Active Top Secret Clearance
• 5+ years of software development experience.
• 2+ years developing Generative AI or Machine Learning applications.
• Strong Python development experience.
• Experience working with Large Language Models including GPT, Llama, Claude, Mistral, or similar models.
• Experience with prompt engineering and AI workflow development.
• Experience building APIs using FastAPI, Flask, or similar frameworks.
• Experience deploying cloud-native applications in Microsoft Azure.
• Familiarity with containerization technologies including Docker and Kubernetes.
• Experience with Git, CI/CD pipelines, and DevSecOps practices.
• Strong understanding of software architecture and distributed systems.

Preferred Qualifications

• Experience with Azure OpenAI Service.
• Experience building Retrieval-Augmented Generation (RAG) systems.
• Knowledge of LangChain, LangGraph, Semantic Kernel, LlamaIndex, or similar orchestration frameworks.
• Experience with vector databases such as Pinecone, Milvus, pgvector, Azure AI Search, or Chroma.
• Experience developing AI agents and autonomous workflows.
• Familiarity with MCP (Model Context Protocol) and agent interoperability concepts.
• Experience with model evaluation, observability, and prompt optimization.
• Experience deploying AI solutions in secure or classified environments.
• Familiarity with Infrastructure as Code using Terraform or Bicep.
• Knowledge of Azure Machine Learning, Azure AI Foundry, or Azure Cognitive Services.