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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Antra, Inc - **Location:** Sterling, VA, United States - **Experience:** Expert - **Salary:** $85,000 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Testing (Software), AI Evaluation, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Computer Programming, Databases, Continuous Integration, Software Debugging, Document Retrieval, Information Retrieval, Python (Programming Language), Machine Learning, OpenAI, Tensorflow, Search Technologies, Software Engineering, SQL Databases, Unstructured Data, Data Logging, Pinecone, Enterprise Software Applications, Microsoft Power Automate, Pytorch, Retrieval-Augmented Generation, Flask (Web Framework), Large Language Models, Multi-Agent Systems, Prompt Engineering, Apache Spark, Hallucination Detection, Model Validation, Llamaindex, Generative AI, Backend, Agentic-AI, Git, Fastapi, Microsoft Copilot Studio, Pyspark, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, FAISS, Claude, Restful APIs, Model Context Protocol, Model Inference, GPT, Data Pipelines, Docker, ChromaDB - **Published:** October 15, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9d46eeb55d14c6a2 ## About the Role Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience. 3+ years of relevant software engineering, AI/ML, or application development experience. Strong programming skills in Python and experience building backend applications or APIs. Hands-on experience with LLMs, Generative AI, or machine learning applications. Understanding of RAG architectures, embeddings, semantic search, and vector databases. Experience with at least one AI development framework, such as LangChain, LangGraph, or LlamaIndex. Experience developing REST APIs using FastAPI, Flask, or similar frameworks. Familiarity with cloud platforms, preferably AWS or Azure. Knowledge of Git, software testing, debugging, and collaborative development practices. Strong analytical, problem-solving, and communication skills. Preferred Qualifications Experience building AI agents, agentic workflows, or multi-step AI automation. Familiarity with Model Context Protocol (MCP), tool calling, and agent orchestration. Experience with AWS Bedrock, Amazon SageMaker, Azure OpenAI, or Azure AI Foundry. Familiarity with vector databases such as FAISS, Pinecone, or ChromaDB. Knowledge of machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn. Experience with Docker, Kubernetes, CI/CD, or MLOps/LLMOps practices. Familiarity with SQL, data pipelines, Apache Spark, or PySpark. Experience with Microsoft Copilot Studio, Power Automate, or conversational AI solutions. Knowledge of AI evaluation, hallucination mitigation, data privacy, and responsible AI practices. What We're Looking For Mid-Level Engineers: Strong hands-on development skills, a solid understanding of LLMs and RAG, and the ability to build and maintain AI applications with appropriate guidance. Senior Engineers: Deeper experience designing production AI solutions, optimizing RAG and agent workflows, making technical decisions, and supporting deployment and performance improvements. Candidates do not need to have experience with every technology listed. Strong Python development skills and practical experience building AI applications are the primary priorities., * Copilot Studio: 4 years (Required) * Contact Center: 4 years (Required) Work Location: Hybrid remote in Sterling, VA 20166 ## Description We are seeking a talented AI Engineer to design, develop, and deploy AI-powered applications using modern Artificial Intelligence and Generative AI technologies. The ideal candidate will have hands-on experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and Python-based application development. The candidate will work with engineering and business teams to build intelligent applications, integrate AI capabilities into existing systems, and deliver scalable, reliable solutions for real-world business problems., Design, develop, and maintain AI-powered applications using Python and modern AI frameworks. Integrate Large Language Models (LLMs), including GPT, Claude, Llama, or similar models, into enterprise applications. Build and optimize RAG pipelines using embeddings, vector databases, semantic search, and document retrieval. Develop AI agents and intelligent workflows using frameworks such as LangChain, LangGraph, or similar technologies. Implement prompt engineering, tool calling, and model evaluation techniques to improve AI response quality and reliability. Develop REST APIs and backend services to integrate AI solutions with enterprise applications, databases, and external systems. Work with structured and unstructured data to support AI applications, knowledge retrieval, and model inference. Deploy and maintain AI applications on cloud platforms such as AWS or Microsoft Azure. Test, troubleshoot, and optimize AI applications for accuracy, performance, scalability, and cost efficiency. Implement logging, monitoring, security controls, and appropriate safeguards for production AI systems. Collaborate with software engineers, data engineers, and business stakeholders to translate requirements into practical AI solutions.