Artificial Intelligence Lead [Remote]

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an Artificial Intelligence Lead based in the United States.

This is a senior AI leadership opportunity supporting the modernization of a large-scale federal acquisitions platform.
You will define the technical AI strategy and lead the integration of advanced machine learning capabilities into secure, cloud-based systems.
A key focus will be designing and orchestrating multiple AI agents into a cohesive ecosystem that supports automation and decision-making while preserving human oversight.
You will guide production AI/ML delivery, MLOps, cloud deployment, and DevSecOps practices across complex enterprise environments.
The role combines hands-on technical leadership with responsibility for federal AI governance, security, transparency, and compliance.
You will collaborate with multidisciplinary teams and communicate complex AI concepts, risks, and tradeoffs to both technical and executive stakeholders.
The position is primarily remote, with travel to Washington, D.C. required as needed to support client and program objectives.

Accountabilities

• Serve as the primary technical authority for AI architecture, research, strategy, and implementation across the program.
• Define and oversee the technical approach for integrating, coordinating, and orchestrating multiple AI agents within a unified and scalable ecosystem.
• Align AI initiatives with program objectives, modernization priorities, business requirements, and federal acquisition goals.
• Evaluate emerging AI and machine learning technologies and determine how they can be applied responsibly to improve automation, efficiency, and decision support.
• Lead the design, development, deployment, and ongoing improvement of scalable AI/ML models in production environments.
• Establish and manage MLOps practices covering model versioning, validation, monitoring, deployment, governance, and lifecycle management.
• Integrate AI and model development workflows into CI/CD pipelines to support reliable, repeatable, and secure production releases.
• Ensure AI solutions are scalable, reliable, performant, maintainable, and appropriately integrated into enterprise cloud environments.
• Deploy and manage AI workloads within secure AWS environments while applying cloud architecture and security best practices.
• Integrate security controls throughout the AI lifecycle in accordance with DevSecOps principles, secure coding standards, identity and access controls, and organizational requirements.
• Align AI implementations with federal IT standards, agency governance requirements, cybersecurity frameworks, and applicable compliance obligations.
• Apply the NIST AI Risk Management Framework and related cybersecurity guidance to AI design, development, deployment, and operations.
• Support security documentation, controls, and evidence required for Authorization to Operate (ATO) processes involving cloud-based systems.
• Promote responsible and ethical AI adoption by ensuring data provenance, model transparency, explainability, auditability, and appropriate human oversight.
• Lead and mentor multidisciplinary technical teams as needed, establishing consistent engineering practices and fostering innovation and experimentation.
• Communicate AI capabilities, technical risks, limitations, and architectural tradeoffs clearly to technical teams, leadership, government stakeholders, and other non-technical audiences.
• Partner with program and technical leadership to maintain security, governance, compliance, and audit readiness throughout the AI lifecycle.

Requirements

• Demonstrated experience serving as an AI Lead, AI Architect, or equivalent senior technical role on complex enterprise or federal technology programs.
• Advanced knowledge of artificial intelligence, machine learning, deep learning, and data science concepts; a Master’s or Ph.D. in a relevant discipline is strongly preferred.
• Proven track record designing, developing, deploying, and managing AI/ML solutions in production environments.
• Hands-on experience implementing MLOps practices, including model lifecycle management, monitoring, validation, versioning, and deployment automation.
• Experience integrating machine learning and AI deployment workflows into modern CI/CD pipelines.
• Strong experience deploying and managing AI workloads within AWS cloud environments.
• Familiarity with cloud security, DevSecOps practices, secure software development, access controls, and enterprise cloud architectures.
• Strong understanding of federal IT standards, AI governance frameworks, cybersecurity requirements, and Authorization to Operate (ATO) processes.
• Experience applying risk management and governance principles to AI systems, particularly in regulated, security-sensitive, or compliance-driven environments.
• Familiarity with multi-agent AI architectures, autonomous workflows, agent orchestration, and emerging generative AI technologies is highly desirable.
• Experience supporting federal AI modernization initiatives, particularly within large government agencies, is preferred.
• Ability to evaluate emerging technologies and translate them into practical, secure, and scalable enterprise solutions.
• Strong leadership, collaboration, mentoring, and stakeholder management capabilities across multidisciplinary teams.
• Excellent written and verbal communication skills, with the ability to explain sophisticated AI concepts and technical tradeoffs to both technical and non-technical audiences.
• Relevant certifications in cloud computing, AI/ML, cybersecurity, or related disciplines are a plus.
• Must be a U.S. citizen and meet eligibility requirements for a U.S. Government security clearance. Applicants who already hold a security clearance or are eligible to obtain one will be considered.

Benefits

• Target salary range of $148,301–$255,653 , with final compensation determined by factors including experience, education, skills, certifications, location, internal equity, client requirements, and security clearance considerations.
• Primarily remote/home-office work environment.
• Opportunity to work on high-impact federal AI modernization initiatives.
• Exposure to advanced AI/ML, multi-agent architectures, MLOps, AWS cloud technologies, and secure DevSecOps environments.
• Opportunity to provide strategic technical leadership across complex, mission-critical programs.
• Collaborative environment involving multidisciplinary technical teams and senior government and program stakeholders.
• Equal employment opportunity and consideration for qualified applicants.
• Reasonable workplace accommodations available for qualified individuals with disabilities.

How Jobgether works:

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.