AI Engineering & Cybersecurity Capability Lead

ECS Federal•WASHINGTON, DC

About The Position

Everforth ECS Federal is seeking a Senior AI Engineering & Cybersecurity Capability Lead to direct the strategy, technical development, and operational integration of artificial intelligence across enterprise cybersecurity missions for Federal agencies. The role leads a specialized AI engineering team developing, integrating, and deploying AI/ML capabilities for Red Team, Blue Team, Purple Team, and Enterprise Vulnerability Management operations. This customer-facing technical leadership position combines hands-on AI engineering with strategic planning. The lead works with section chiefs, customer executive leadership, cybersecurity operators, and technical stakeholders to set the direction, architecture, and delivery priorities for AI-enabled cybersecurity capabilities, and to turn emerging technologies into practical, mission-ready solutions. The role includes setting an AI capability roadmap; advising program and executive leadership; leading AI/ML architecture, engineering, integration, and deployment; and guiding capabilities from proof of concept through operational deployment and sustained operations. Technologies and use cases include LLMs, agentic AI, RAG, machine learning, model optimization, workflow automation, threat hunting, adversary emulation, vulnerability prioritization, security analytics, incident response, and defensive automation. The lead also oversees secure AI infrastructure and integrations with enterprise cybersecurity platforms, establishes engineering standards, mentors a multidisciplinary team, and embeds AI into existing operational workflows. Solutions must address the security, governance, and operational requirements of classified customer environments and comply with applicable FBI security requirements, RMF, NIST AI RMF, data governance, and responsible AI principles.

Requirements

Active Top Secret security clearance.
10+ years of relevant technical experience, including at least 2 years in a technical leadership or management capacity.
Demonstrated experience leading AI/ML engineering initiatives from solution architecture through production deployment.
Strong hands-on experience with LLMs, agentic AI frameworks, RAG architectures, machine learning, and AI automation.
Proficiency in Python, API development, systems integration, data engineering, and modern software development practices.
Experience designing and implementing AI solutions within secure enterprise environments.
Working knowledge of cybersecurity operations, including threat detection, vulnerability management, incident response, or offensive/defensive security.
Demonstrated ability to lead technical teams, establish engineering direction, and mentor senior engineers.
Experience advising senior technical or executive stakeholders and translating complex engineering concepts into mission outcomes.

Responsibilities

Establish and execute the AI capability roadmap, aligning engineering priorities, investments, and implementation milestones with cybersecurity objectives.
Advise program leadership, Section Chiefs, and executive stakeholders on emerging technologies, operational opportunities, and AI-related risks.
Translate cybersecurity mission challenges into AI engineering initiatives, measurable outcomes, and scalable enterprise solutions.
Evaluate emerging AI/ML technologies, commercial products, open-source frameworks, and industry advancements for innovation opportunities.
Set technical priorities and guide capabilities from proof of concept through initial operational capability, full operational capability, and sustained operations.
Communicate technical progress, mission impact, operational risks, and strategic recommendations to senior leadership.
Lead the architecture, development, integration, and deployment of AI/ML solutions for offensive and defensive cybersecurity operations.
Provide hands-on technical leadership in LLMs, agentic AI, RAG, machine learning, model optimization, and intelligent workflow automation.
Guide development of AI-enabled capabilities for threat hunting, adversary emulation, vulnerability prioritization, security analytics, incident response, and defensive automation.
Direct integration of AI solutions with SIEM/SOAR, vulnerability management tools, threat intelligence sources, and security assessment technologies.
Oversee secure AI infrastructure, including private model hosting, GPU environments, air-gapped deployments, data pipelines, and model orchestration.
Advance capabilities to detect and respond to AI-enabled adversarial activity, including automated reconnaissance, adaptive attacks, prompt injection, and model exploitation.
Establish engineering standards for AI solution reliability, evaluation, testing, observability, security, and operational performance.
Balance innovation with security, governance, and operational requirements for classified customer environments.
Lead, mentor, and develop AI engineers and technical specialists, fostering technical excellence, innovation, collaboration, and accountability.
Set engineering workstreams, delivery priorities, technical milestones, and performance expectations.
Build partnerships between AI engineers and Red, Blue, Purple, SOC, and Vulnerability Management teams to ensure solutions meet operational needs.
Guide technical design reviews, architecture decisions, engineering troubleshooting, and resolution of complex implementation challenges.
Develop team capabilities through mentoring, technical knowledge sharing, training, and exposure to emerging AI engineering practices.
Manage technical priorities and resources while maintaining delivery momentum and responsiveness to mission requirements.
Establish repeatable processes for moving AI solutions from experimentation into secure, supportable production environments.
Identify opportunities to reduce manual effort, improve analytical accuracy, accelerate threat identification, and strengthen enterprise cybersecurity visibility.
Integrate AI capabilities into existing cybersecurity workflows, tools, and operational processes.
Collaborate with government system owners, security stakeholders, infrastructure teams, and mission operators to support secure and sustainable implementation.
Establish measurable performance indicators for operational efficiency, threat detection, vulnerability remediation, and analyst effectiveness.
Support cybersecurity exercises, incident response activities, and enterprise security initiatives with AI-enabled analytics and decision-support capabilities.
Ensure solutions comply with applicable FBI security requirements, RMF, NIST AI RMF, data governance, and responsible AI principles.