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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead AI Architect (Intelligence Center) - **Company:** MITRE Corporation - **Location:** McLean, VA, United States - **Experience:** Expert - **Salary:** $174,000.0 - $217,500.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Systems Engineering, Cloud Computing Security, Cloud Engineering, Cyber Security, Data Architecture, Information Engineering, Information Leak Prevention, Machine Learning, Open Source Technology, Azure Machine Learning, Software Engineering, Retrieval-Augmented Generation, Large Language Models, Generative AI, Agentic-AI, Togaf, Data Analytics, Machine Learning Operations, Prompt Injection, Azure AI, Devsecops - **Published:** October 26, 2026 - **Apply:** https://www.techcareers.com/job.asp?id=3468782749&tx=JK3529FFP&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54 ## About the Role * Typically requires a minimum of 8 years experience in AI with a Bachelor's degree in a relevant field; or 6 years and a Master's degree. * Demonstrated experience with AI-enabled systems across the capability lifecycle including research and development, strategy, policy, acquisition, systems engineering, test and evaluation, operations, program management, technology transition, or sustainment * Experience supporting technical research, systems engineering, software engineering, cybersecurity, data analytics, AI/ML, or emerging technology initiatives. * Working knowledge of AI, Machine Learning, Generative AI, Large Language Models, or related emerging technologies. * Experience analyzing technical concepts, systems, or capabilities and communicating findings through written reports, briefings, or technical documentation. * Ability to evaluate technical information and develop clear, evidence-based findings and recommendations. * Ability to work collaboratively with multidisciplinary technical teams and government stakeholders. * Ability to understand complex technical concepts and translate them into strategic recommendations for a range of audiences * Demonstrated ability to shape and define work in collaboration with sponsors or stakeholders, even in the absence of fully defined requirements * Demonstrated leadership skills, including leading teams, developing and managing schedules, communicating risks, and managing budgets * Strong written and verbal communication skills, including the ability to communicate complex technical concepts to a range of audiences. * Must have an active Top Secret/SCI w/Poly U.S Government issued Security Clearance. Per the U.S. Government's eligibility requirements, you must be a U.S Citizen to be considered for a security clearance. * This position has an on-site requirement of 5 days a week on-site., * Experience supporting Intelligence Community, Department of Defense, or other national security missions. * Experience evaluating or implementing AI/ML, Generative AI, LLM, RAG, agentic AI, or autonomous system capabilities. * Experience supporting AI engineering, systems engineering, solution architecture, cloud engineering, data engineering, DevSecOps, MLOps, or LLMOps. * Experience evaluating emerging technologies, commercial products, government-developed capabilities, or open-source solutions for enterprise or mission use. * Experience supporting technology pilots, prototypes, demonstrations, operational evaluations, or transition-to-production activities. * Knowledge of AI security, including model security, adversarial AI, prompt injection, data leakage, AI supply-chain risks, or AI red teaming. * Familiarity with Responsible AI, AI governance, model risk management, or the NIST AI Risk Management Framework (AI RMF). * Experience developing technology assessments, architecture documentation, technical risk assessments, executive briefings, or investment recommendations. * Experience working in classified environments, secure cloud environments, or with national security systems. * Relevant technical or professional certifications such as AWS Machine Learning, Azure AI Engineer, Google Professional Machine Learning Engineer, NVIDIA AI, TOGAF, CISSP, PMP, SAFe, or AI governance/risk management certifications. This requisition requires the candidate to have a minimum of the following clearance(s) ## Description * Support the evaluation, engineering, integration, and implementation of Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and other emerging technology capabilities. * Assess commercial, government, and open-source AI technologies to identify potential mission applications, capability gaps, risks, and modernization opportunities. * Support the development and evaluation of AI solution architectures, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic AI, data architectures, and cloud-based AI solutions. * Assist engineering teams with the design, integration, testing, and technical assessment of AI capabilities in laboratory, pilot, and operational environments. * Support AI test, evaluation, verification, and validation (TEVV), including performance benchmarking, operational testing, robustness assessments, and mission suitability evaluations. * Review technical designs, engineering approaches, implementation plans, and test results to assess technical readiness and identify risks or areas for improvement. * Support pilot activities, demonstrations, and technology evaluations, including development of use cases, test criteria, technical findings, and recommendations. * Research emerging AI technologies and industry trends and translate findings into actionable recommendations for technical and executive stakeholders. * Support secure and responsible AI implementation, including AI security, risk management, model governance, data protection, and compliance with applicable policies and standards. * Develop technical documentation, technology assessments, decision briefings, engineering reports, and other products that communicate findings and recommendations to technical and non-technical audiences. * Collaborate with engineers, architects, cybersecurity professionals, program managers, mission stakeholders, and government sponsors to transition promising technologies into operational use.