Senior AI Solutions Architect

Roles & Responsibilities

• Engage technical and mission users to understand objectives, workflows, data needs, security constraints, and adoption challenges;
• Translate those needs into AI solution concepts, prototypes, integration plans, reusable patterns, and implementation guidance.
• Design, develop, integrate, test, and document AI-enabled applications and workflows using approved AI tools, services, APIs, agents, retrieval-enabled approaches, data integrations, and developer environments.
• Help teams move beyond isolated AI experiments toward secure, supported, responsible, and repeatable use of AI in mission, engineering, analytic, software-development, and operational workflows.
• Independently evaluate AI solution alternatives and technical tradeoffs using multiple sources of information; identify risks, dependencies, gaps, and practical paths forward across approved data and security environments.
• Develop and promote reusable AI workflows, prompt patterns, agentic components, starter kits, development-environment templates, technical guidance, and enablement knowledge that make approved capabilities easier to discover, learn, access, integrate, and apply.
• Deliver demonstrations, training, office hours, hands-on experimentation, and high-touch technical support; identify recurring user needs and feedback that improve tools, support models, and adoption pathways.
• Collaborate across MITRE with mission users, AI communities, platform teams, Enterprise Technology, Information Security Services, laboratories, software, data, and systems engineering communities, and technical leadership; lead defined technical tasks or small efforts and provide knowledge transfer and informal guidance as appropriate.

Basic Qualifications

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree; or 3 years and a Master’s degree; or a PhD with relevant experience who can immediately contribute at this job step; or equivalent combination of related education and work experience.
• Experience designing, developing, integrating, or enabling applied AI solutions, AI/ML workflows, AI-enabled applications, software services, data platforms, developer environments, platform engineering capabilities, or related technical solutions.
• Senior-level technical knowledge in applied AI, AI/ML workflows, LLM APIs, enterprise AI platforms, agentic workflows, data infrastructure, cloud or hybrid platforms, GPU-enabled environments, developer tooling, or related technical domains.
• Experience translating user, project, or mission needs into reusable technical solutions, workflows, patterns, prototypes, data integrations, implementation guidance, training, or enablement models.
• Ability to work independently with minimal guidance, analyze multiple sources of information to solve complex technical problems, communicate complex information clearly, build consensus, and collaborate with technical and nontechnical stakeholders.
• Must be eligible to obtain and maintain a Top Secret/SCI U.S Government issued Security Clearance within one year of hire.
• Ability to work a hybrid schedule with a minimum of 3 days on-site presence per week in McLean, VA; Bedford, MA; Colorado Springs, CO; San Diego, CA; Omaha, NE; Ft. Meade, MD; Charlottesville, VA; or Los Angeles, CA and travel up to 5%.

Preferred Qualifications

• Graduate degree in computer science, artificial intelligence, machine learning, data science, software engineering, systems engineering, human-centered computing, or a related technical field.
• Experience with LLM APIs, enterprise AI platforms, agentic tools, MCP services, Agent Skills, MLOps, LLMOps, Kubernetes, Kubeflow, GPU environments, retrieval-enabled systems, AI application development, or AI-enabled developer experiences.
• Hands-on experience designing, prototyping, integrating, testing, or documenting AI applications, agentic workflows, retrieval-enabled solutions, reusable prompt patterns, starter kits, data integrations, or development-environment templates.
• Experience helping technical or mission users adopt AI tools through training, coaching, internal enablement programs, communities of practice, office hours, rapid prototyping events, VibeLab-style challenges, or hands-on experimentation.
• Experience integrating AI capabilities with software delivery, DevSecOps, data platforms, analytics, modeling and simulation, systems engineering, knowledge management, or mission workflow platforms.
• Experience supporting AI workloads across on-prem, hybrid, cloud, CUI-capable, classified-adjacent, or other controlled computing environments.
• Experience with data intake, curation, exchange, governance, retrieval, secure data workflows, or mission AI data pipelines.
• Experience developing reusable AI patterns, technical guidance, enablement playbooks, quality practices, support models, or other resources that make approved AI capabilities easier to adopt and apply responsibly.
• Active TS/SCI clearance.