Lead AI Architect (Intelligence Center)

Roles & Responsibilities

• 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.

Basic Qualifications

• 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.

Preferred Qualifications

• 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.

Pay

Salary compensation range: $174,000 - $261,000 annually.

This requisition requires the candidate to have a minimum of the following clearance(s): Top Secret/SCI/Polygraph. This requisition requires the hired candidate to have or obtain, within one year from the date of hire, the following clearance(s): Top Secret/SCI/Polygraph.