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# AI Solutions Engineer (Washington DC)

- **Company:** Strategic Inc
- **Location:** Arlington, VA, United States
- **Experience:** Experienced
- **Salary:** $135,000.0 - $165,000.0
- **Contract:** Internship / Graduate position
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Systems Engineering, Microsoft Azure, Computer Programming, Information Engineering, Data Structures, Distributed Computing Environment, Python (Programming Language), Machine Learning, OpenAI, Search Technologies, Software Engineering, SQL Databases, Explainable AI (XAI), Pinecone, Qdrant, LangChain, Retrieval-Augmented Generation, Large Language Models, Prompt Engineering, Apache Spark, Llamaindex, Generative AI, Agentic-AI, Build Management, Containerization, Pyspark, Kubernetes, Information Technology, HuggingFace, Free and Open-Source Software, Milvus, Ollama, Machine Learning Operations, Claude, Asynchronous Programming, GPT, Serverless Computing, Human in the Loop, Docker
- **Published:** October 29, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=ae19b1a0a4459a29

## About the Role

The ideal candidate is a recent top-tier university graduate or early-career engineer with exceptional coding fundamentals, a strong grasp of data structures and ML systems, and a passion for turning state-of-the-art AI research into secure, production-ready federal solutions., * Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

 * 3+ years of hands-on software engineering or AI/ML experience (exceptional new graduates with strong undergraduate research, hackathon wins, or elite internships will be considered).
 * Strong programming proficiency in Python, with a solid understanding of data structures, algorithms, API integration, and asynchronous programming.
 * Demonstrated project or professional experience working with LLMs, prompt engineering paradigms, vector databases (e.g., Pinecone, Milvus, Qdrant), or agentic frameworks (e.g., LangChain, LlamaIndex, LangGraph).
 * Familiarity with Kubernetes and containerization tools (Docker)., * Track record of shipping production-grade code or open-source contributions in machine learning or systems engineering.
 * Hands-on experience deploying open-weight models using vLLM, TGI, or Ollama, and optimizing inference performance.
 * Exposure to distributed data processing frameworks (e.g., Apache Spark / PySpark)cite: 1.
 * Strong appetite for rapid learning, breaking down complex technical ambiguity, and working in a fast-paced government consulting environment.

## Description

Strategic Innovation Group (SIG) is seeking a high-caliber, mathematically grounded, and relentlessly curious Junior to Mid-Level AI/ML Engineer to build next-generation enterprise AI applications for federal civilian clients. Working alongside senior architects and technical leaders, you will design, engineer, and deploy production-grade Large Language Model (LLM) workflows, Retrieval-Augmented Generation (RAG) pipelines, and agentic AI systems. The AI Solutions Engineer will focus on enabling, developing, and innovating within enterprise AI environments, supporting both the architecture and implementation of advanced AI solutions. They will build and deploy AI applications leveraging large language models (LLMs), and agent frameworks., The essential functions include, but are not limited to the following:

 * Design, develop, and deploy scalable AI/ML solutions, including LLM-powered applications, RAG architectures, and agent-based workflows, in complex, enterprise environments.
 * Build and maintain end-to-end ML pipelines (data engineering, model development, deployment, monitoring, and retraining) using Python, SQL, and modern MLOps practices.
 * Develop and integrate AI applications using foundation models (such as Claude, GPT variants, and open-weight Hugging Face models) and cloud-native services across AWS and Azure (e.g., Bedrock, SageMaker, OpenAI Service, AI Search).
 * Design secure, auditable, and explainable AI systems with strong governance, traceability, and human-in-the-loop controls for mission-critical and compliance-sensitive environments.
 * Collaborate with cross-functional teams to prepare data, enable semantic retrieval, and deliver robust AI-driven solutions aligned to operational needs.
 * Continuously monitor, evaluate, and optimize AI system performance to meet client-defined objectives for accuracy, reliability, and scalability.
 * Establish and maintain scalable AI infrastructure using containerization and orchestration tools (Docker, Kubernetes) and CI/CD pipelines.
 * Document solutions and provide knowledge transfer to ensure long-term sustainability and adoption of AI capabilities.