Generative AI Engineer (Clearance Required)

InterImage; Arlington (VA); On-site; USD 150,000 - 210,000; Full time

Job summary

InterImage is seeking engineers to convert Generative AI concepts into production-ready software, focusing on AI-powered applications for mission-critical customers. You will design, develop, deploy, and continuously improve cloud-native AI solutions in Azure, emphasizing secure, scalable architectures and rapid iteration.

You will work with LLMs, Prompts, AI workflows, and APIs, collaborating with software engineers, cloud architects, and data scientists to deliver innovative solutions while

Qualifications

• 5+ years of software development experience.
• 2+ years developing Generative AI or Machine Learning applications.
• Strong Python development experience.
• Experience with Large Language Models (GPT, Llama, Claude, Mistral or similar).
• Experience deploying cloud-native apps in Microsoft Azure.
• Familiarity with containerization (Docker, Kubernetes).
• Experience with Git, CI/CD, and DevSecOps practices.

Responsibilities

• Design and build Generative AI applications using LLMs.
• Develop proof-of-concepts that evolve into production-ready software.
• Architect RAG solutions using vector databases and enterprise data sources.
• Build intelligent agents and AI workflows for reasoning and automation.
• Develop REST APIs and backend services for AI applications.
• Deploy scalable AI solutions in Azure environments.
• Design cloud-native architectures using Azure services and AKS.

Skills

Python

Large Language Models

Prompt Engineering

REST APIs

Azure

Kubernetes

DevSecOps

Distributed Systems

Docker

Git & CI/CD

Tools

Docker

Kubernetes

FastAPI/Flask

LangChain/LangGraph

Azure OpenAI

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.