AI Technical Lead

ECS is seeking an AI Technical Lead to work in our Arlington, VA office.

Job Summary:

We are seeking an accomplished AI Technical Lead to lead a team of twenty (20) AI professionals in advancing secure, resilient, and integrated AI systems across the enterprise. This role combines deep technical expertise in artificial intelligence and machine learning with strong leadership and strategic vision to drive secure-by-design adoption, vulnerability management, and cross-sector AI integration. The AI Technical Lead will spearhead the creation of enterprise AI roadmaps, observability frameworks, and risk-mitigated architectures that enhance reliability, transparency, and security across mission-critical AI deployments. The successful candidate will foster a culture of innovation, collaboration, and proactive risk management aligned with organizational and industry best practices. 

Responsibilities:

• Lead, mentor, and inspire a team of 20 AI engineers, data scientists, and specialists, providing technical direction, performance feedback, and professional growth opportunities. 
• Champion secure-by-design principles in AI development, ensuring that cybersecurity, privacy, and resilience are embedded throughout the system lifecycle. 
• Design and oversee AI vulnerability management strategies, including the identification, assessment, mitigation, and continuous monitoring of risks in models and infrastructure. 
• Drive cross-sector and multi-system AI integration efforts to ensure interoperability, scalability, and consistent security across platforms and domains. 
• Lead the development and execution of comprehensive AI roadmaps, aligning initiatives with mission objectives, technology trends, and compliance requirements. 
• Oversee the design and deployment of observability architectures, tools, and dashboards to monitor model performance, detect anomalies, and maintain data integrity. 
• Partner with product, cybersecurity, and operations teams to deliver integrated AI solutions that balance innovation, security, and operational excellence. 
• Stay current on AI, ML, and security advancements; evaluate new observability and governance tools; and apply findings to improve team capabilities and solution maturity. 
• Manage project timelines, budgets, and resources to ensure timely, high-quality delivery of complex AI initiatives. 
• Potential Deliverables 
• Enterprise AI observability reference architecture incorporating secure-by-design principles for scalable and secure AI monitoring. 
• Custom dashboards and reports providing real-time and historical insights into model health, data drift, and system performance. 
• Standard Operating Procedures (SOPs) for model versioning, rollback, and root-cause analysis to minimize downtime. 
• Incident response playbooks for AI model failures, including anomaly detection, escalation, and recovery protocols. 
• A comprehensive AI roadmap detailing short- and long-term strategic milestones, technology adoption priorities, and AI maturity goals. 
• Comparative tool evaluations of open-source and commercial AI observability platforms to support procurement and integration decisions. 
• Enterprise AI observability reference architecture incorporating secure-by-design principles for scalable and secure AI monitoring. 
• Custom dashboards and reports providing real-time and historical insights into model health, data drift, and system performance. 
• Standard Operating Procedures (SOPs) for model versioning, rollback, and root-cause analysis to minimize downtime. 
• Incident response playbooks for AI model failures, including anomaly detection, escalation, and recovery protocols. 
• A comprehensive AI roadmap detailing short- and long-term strategic milestones, technology adoption priorities, and AI maturity goals. 
• Comparative tool evaluations of open-source and commercial AI observability platforms to support procurement and integration decisions. 

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field. 
• Minimum 5–8 years of experience in AI/ML engineering or related fields. 
• At least 3–5 years of experience in a leadership or technical lead capacity managing teams of 10+ personnel. 
• Demonstrated success in secure AI system design, vulnerability management, and multi-sector AI integration. 
• Proven experience developing and executing AI strategic roadmaps within enterprise or government environments. 
• Deep expertise with AI/ML frameworks (TensorFlow, PyTorch) and cloud platforms (AWS, Azure, Google Cloud). 
• Experience with AI observability tools such as Prometheus, Grafana, ELK Stack, or Datadog. 
• Knowledge of vulnerability scanning, threat modeling, and incident response for AI workloads. 
• Familiarity with AI security standards and regulatory frameworks, including NIST AI RMF and ISO/IEC 42001. 
• Practical understanding of data governance, privacy, and AI ethics considerations. 
• Strong interpersonal, communication, and mentoring skills to guide cross-functional technical teams. 
• Proven ability to translate complex AI and cybersecurity concepts into actionable recommendations for executives and stakeholders. 
• Experience with Agile/Scrum methodologies, backlog prioritization, and risk-based resource management. 
• Must be a U.S. Citizen and eligible to obtain and maintain a Department of Homeland Security (DHS) EOD clearance (requires a favorable background investigation).