> Markdown version of [/jobs/ext/3876638-agentic-ai-architect](https://www.wearedevelopers.com/jobs/ext/3876638-agentic-ai-architect). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Agentic AI Architect - **Company:** XMS Solutions Inc - **Location:** Washington, DC, United States - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Python (Programming Language), Software Deployment, Software Engineering, Systems Integration, Data Logging, Google Cloud, Enterprise Software Applications, Chatbots, LangChain, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Generative AI, Agentic-AI, AI Platforms, Kubernetes, Deployment Automation, AutoGen, Machine Learning Operations, Virtual Agents, Evaluation of Large Language Models, Model Context Protocol, Semantic Kernel, Devsecops, Human in the Loop - **Published:** October 22, 2026 - **Apply:** https://www.clearancejobs.com/jobs/9255029/agentic-ai-architect ## About the Role * Professional experience in solution architecture, software engineering, AI engineering, or a closely related technical discipline. * Hands-on experience building or integrating generative AI solutions using LLMs, including an understanding of their capabilities and limitations. * Experience with Python, APIs, and integrations involving enterprise applications or data sources. * Experience integrating and deploying chatbots in Microsoft Teams or comparable enterprise platforms. * Working knowledge of RAG, vector databases, AI agents, and orchestration concepts. * Experience designing and deploying applications in Azure, AWS, or Google Cloud, with attention to security and maintainability. * Ability to work collaboratively across engineering and business teams and move solutions beyond proof of concept. Preferred Qualifications * Experience with multi-agent frameworks, autonomous workflows, or human-in-the-loop automation. * Familiarity with LangChain, LangGraph, Semantic Kernel, AutoGen, Model Context Protocol (MCP), or similar technologies. * Experience with LLM evaluation, observability, model security, or AI governance practices. * Familiarity with cloud AI services, DevSecOps, deployment automation, or MLOps. * Experience supporting enterprise-scale AI deployments and integrations across multiple applications. ## Description XMS Solutions is seeking an Agentic AI Architect to design and help deliver practical, next-generation AI solutions. In this hands-on role, you will help build intelligent assistants, agent-based workflows, and enterprise AI applications using generative AI, large language models (LLMs), and modern cloud technologies. You will collaborate with engineers, cybersecurity professionals, and business stakeholders to turn emerging AI capabilities into secure, scalable solutions that work in real-world environments. This position offers meaningful architecture ownership and an opportunity to contribute to the organization's evolving AI approach. Key Responsibilities * Design and develop agentic AI solutions, including intelligent agents, multi-agent workflows, AI assistants, and human-in-the-loop processes. * Translate business and technical requirements into practical architectures, implementation plans, and reusable patterns. * Evaluate and apply LLMs, RAG, vector databases, and orchestration frameworks based on solution needs and technical tradeoffs. * Integrate AI capabilities with enterprise applications, APIs, data sources, and existing business workflows. * Build, integrate, and deploy AI-powered chatbots and virtual assistants in Microsoft Teams and other enterprise applications. * Partner with engineering teams to take AI prototypes through testing, deployment, monitoring, and production support. * Collaborate with cloud, data, cybersecurity, and application teams to deliver secure and maintainable implementations. * Incorporate appropriate access controls, testing, logging, evaluation, and responsible AI practices into solutions. * Document designs, share recommendations, and communicate technical decisions clearly with project stakeholders.