dreamwork_

Everforth ECS Federal is seeking a Senior AI Engineering & Cybersecurity Capability Lead to drive the strategy, technical development, and operational integration of artificial intelligence across enterprise level cybersecurity missions for Federal agencies. 

 

In this role, you will lead a specialized AI engineering team responsible for developing, integrating, and deploying advanced AI/ML capabilities supporting Red Team, Blue Team, Purple Team, and Enterprise Vulnerability Management operations. The ideal candidate combines deep, hands-on AI engineering expertise with strategic vision, strong technical leadership, and the ability to translate emerging technologies into practical, mission-ready solutions. Working directly with section chiefs, customer executive leadership, cybersecurity operators, and technical stakeholders, this leader will establish the direction, architecture, and delivery priorities for AI-enabled cybersecurity capabilities. This is a customer facing, technical leadership role requiring someone who can shape the future of AI-enabled cyber operations while remaining actively engaged in engineering, innovation, and delivery.

 

Key Responsibilities include:

  1. Strategic Direction & Executive Engagement
  • Establish and execute the AI capability roadmap, aligning engineering priorities, investments, and implementation milestones with cybersecurity objectives.
  • Serve as the principal AI technical advisor to program leadership, Section Chiefs, and executive stakeholders on emerging technologies, operational opportunities, and AI-related risks.
  • Translate complex cybersecurity mission challenges into actionable AI engineering initiatives, measurable outcomes, and scalable enterprise solutions.
  • Evaluate emerging AI/ML technologies, commercial products, open-source frameworks, and industry advancements to identify opportunities for innovation.
  • Define technical priorities and guide progression from proof of concept through initial operational capability (IOC), full operational capability (FOC), and sustained operations.
  • Communicate technical progress, mission impact, operational risks, and strategic recommendations to senior leadership.
  1. Technical Architecture, Engineering & Innovation
  • Lead the architecture, development, integration, and deployment of AI/ML solutions supporting 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 enterprise cybersecurity platforms, including 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 for detecting and responding 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 technical innovation with security, governance, and operational requirements applicable to classified customer environments.
  1. Team Leadership & Operational Delivery
  • Lead, mentor, and develop a multidisciplinary team of AI engineers and technical specialists, fostering technical excellence, innovation, collaboration, and accountability.
  • Establish clear engineering workstreams, delivery priorities, technical milestones, and performance expectations.
  • Build strong partnerships between AI engineers and existing Red, Blue, Purple, SOC, and Vulnerability Management teams to ensure solutions address real operational requirements.
  • 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 competing 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.
  1. Enterprise Integration & Mission Impact
  • Identify opportunities to reduce manual effort, improve analytical accuracy, accelerate threat identification, and strengthen enterprise cybersecurity visibility.
  • Lead integration of AI capabilities into existing cybersecurity workflows, tools, and operational processes rather than creating disconnected solutions.
  • Collaborate with government system owners, security stakeholders, infrastructure teams, and mission operators to ensure secure and sustainable implementation.
  • Establish measurable performance indicators demonstrating improvements in operational efficiency, threat detection, vulnerability remediation, and analyst effectiveness.
  • Support major cybersecurity exercises, incident response activities, and enterprise security initiatives through 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.

 

Salary Range: $215,000 - $240,000

General Description of Benefits



  • 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 modern AI technologies, including 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
This listing is tracked by dreamwork from public job postings. Want it prepared into a personalized application pack? Upload your resume →
Posted yesterday