Department Summary:Mission Computing, L080, is a new division being established to accelerate how MITRE turns technical possibility into mission capability. We're bringing together supercomputing, AI services, secure lab and cloud infrastructure, and modern engineering tooling, all organized as a front-line function that shapes how teams across MITRE build, experiment, and deliver. The AI and Mission Enablement department is the applied AI and services adoption arm of Mission Computing. Its role is to make MITRE's AI and mission platform investments practical for mission work: giving staff usable paths to approved tools, workflows, reusable patterns, data integrations, development environments, hands-on experimentation, and high-touch technical support. The department helps teams move beyond isolated experiments into secure, repeatable ways of using platforms and computing environments in all aspects of their work.
As Mission Computing stands up, AI and Mission Enablement will sit between infrastructure and practice. The department will work with platform teams, mission users, laboratories, Enterprise Technology, Information Security Services, and AI communities across MITRE to standardize how capabilities are discovered, integrated, taught, supported, and scaled across approved data and security environments. Its work is to make AI and platforms easier to learn, easier to trust, easier to connect to MITRE workflows, and easier to apply responsibly to mission problems. AI Enablement is the group that turns platforms, APIs, agents, data workflows, secure compute, and developer experiences into a working foundation for a mission-centric MITRE.
Roles & Responsibilities:MITRE's AI and Mission Enablement Department within the Mission Computing Division is seeking a Lead AI Solutions Architect to serve as a lead-level technical individual contributor within AI Enablement. The Lead AI Solutions Architect will provide technical direction for complex, cross-functional efforts that turn approved AI platforms, APIs, agents, data workflows, secure computing environments, and developer experiences into practical and repeatable mission solutions. Roles and responsibilities include:
- Lead discovery and solution-architecture engagements for complex, ambiguous, or cross-cutting mission needs; establish objectives, scope, success measures, decision criteria, and an effective path from experimentation through implementation and adoption.
- Develop and lead solution strategies and executable architectures that integrate AI applications, agentic workflows, retrieval-enabled systems, approved data sources, secure computing environments, developer tooling, platform services, and mission workflows.
- Direct technical evaluations and trade studies, synthesize multiple sources of information, identify risks and dependencies, and recommend innovative but practical approaches for secure, supported, responsible, and repeatable AI use.
- Lead functional teams, technical workstreams, or complex projects with moderate resource requirements, risks, dependencies, or organizational complexity; establish technical strategies and objectives and guide multidisciplinary contributors in their execution without formal supervisory authority.
- Establish and promote reusable AI workflows, prompt patterns, agentic components, starter kits, development-environment templates, data-integration approaches, technical standards, quality practices, and support models that improve adoption and scale impact across programs.
- Mature AI enablement practices, including capability discovery, intake, experimentation, onboarding, training, office hours, technical support, feedback loops, and transition from prototypes to supported use; identify recurring needs and opportunities to improve or scale services.
- Advise mission users, project leaders, platform teams, security stakeholders, and senior technical leaders on AI solution alternatives, constraints, sequencing, resource needs, and long-term implications; provide architecture review, mentoring, knowledge transfer, and cross-MITRE collaboration.
Basic Qualifications:- Minimum of 8 years of related experience with a bachelor's degree; or 6 years and a master's degree; or a PhD with 3 years' experience; or equivalent combination of related education and work experience.
- Extensive experience in applied AI, AI/ML workflows, AI-enabled applications, software engineering, data platforms, developer services, platform engineering, research computing, mission computing, or related technical domains, with working knowledge of related disciplines.
- Experience leading functional teams, technical workstreams, or complex projects with moderate resource requirements, risks, dependencies, or organizational complexity; developing technical strategies and objectives and guiding execution without formal people-management authority.
- Experience translating ambiguous user, project, or mission needs into executable AI solution architectures, reusable technical services, workflows, patterns, prototypes, data integrations, enablement models, implementation plans, or adoption roadmaps.
- Ability to work independently with guidance only in the most complex situations, lead others in solving complex technical problems, communicate complex concepts clearly, build consensus, and influence technical users, project leaders, platform teams, security or compliance stakeholders, and senior leadership.
- Must be eligible to obtain and maintain a Secret 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.
- Ability to work a minimum 3 days per-week on-site presence in McLean, VA or Bedford, MA 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 leading complex, customer-facing AI enablement, AI solution architecture, capability-adoption, technical-consulting, or platform-integration efforts involving multiple organizations, technical disciplines, or stakeholder communities.
- Extensive 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.
- Experience leading the design, integration, and operationalization of AI capabilities across software delivery, DevSecOps, data platforms, analytics, modeling and simulation, systems engineering, knowledge management, or mission workflow platforms.
- Experience leading AI workloads or solution architectures across on-prem, hybrid, cloud, CUI-capable, classified-adjacent, or other controlled computing environments.
- Experience establishing secure and repeatable approaches for data intake, curation, exchange, governance, retrieval, AI data pipelines, or other mission AI data workflows.
- Experience establishing or improving AI training, coaching, internal enablement programs, communities of practice, office hours, rapid prototyping events, VibeLab-style challenges, hands-on experimentation, or related adoption mechanisms.
- Experience establishing reusable AI patterns, technical standards, architecture-review practices, starter kits, development templates, enablement playbooks, quality practices, or support models and transferring those practices to other technical staff.
- Active Secret or higher Security Clearance.
This requisition requires the candidate to have a minimum of the following clearance(s):None
This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s):Secret
Salary compensation range and midpoint:$174,000 - $217,500 - $261,000 Annual
Work Location Type:Onsite
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