Lead AI Infrastructure Engineer

Lead AI Infrastructure Engineer

Location: Annapolis Junction, MD
Clearance: TS/SCI with Polygraph required
Work Type: On-site
Salary: $293,000-$306,000

We are seeking an experienced Lead AI Infrastructure Engineer to provide technical leadership for the design, deployment, and operation of enterprise artificial intelligence and machine learning platforms. This role will lead the development and sustainment of critical AI infrastructure components, with a focus on scalable model deployment, platform reliability, and support for AI-enabled applications and services.

The successful candidate will combine hands‑on engineering expertise with team leadership responsibilities, serving as a technical lead for platform initiatives while supporting the professional development of engineering staff. This position requires strong cloud engineering, platform architecture, and organizational leadership skills to drive innovation, operational excellence, and technology adoption across multiple teams.

• Design, implement, and optimize infrastructure supporting large‑scale AI model deployment and inference services.
• Lead the development, deployment, and maintenance of production AI applications and platform services.
• Serve as the technical lead for AI infrastructure initiatives, coordinating activities across engineering teams and stakeholders.
• Provide mentorship, coaching, and professional development support to engineering team members.
• Support team operations, resource planning, and administrative coordination activities.
• Define technical solutions for complex and evolving requirements.
• Establish and maintain technical standards, policies, governance processes, and engineering best practices.
• Drive adoption of emerging technologies, automation capabilities, and platform modernization initiatives.
• Design, implement, and oversee monitoring, logging, alerting, and observability solutions.
• Ensure the reliability, availability, scalability, performance, and security of AI platform components.
• Communicate technical strategies, project status, and recommendations to stakeholders at multiple organizational levels.
• Lead troubleshooting, root cause analysis, and continuous improvement efforts for production systems.

• Bachelor's degree in Computer Science, Software Engineering, Information Systems, Computer Engineering, or a related technical discipline and twelve (12) years of relevant experience; OR
• Four (4) additional years of directly related experience may be substituted for the degree requirement.

• Extensive experience designing, building, deploying, and operating enterprise‑scale production systems.
• Deep expertise in systems integration across diverse technologies, platforms, and cloud environments.
• Hands‑on experience designing, deploying, and managing cloud infrastructure within Amazon Web Services (AWS).
• Advanced experience administering and deploying applications using Kubernetes.
• Strong software development skills using Python.
• Experience implementing and scaling observability solutions using technologies such as:
  • Application Performance Monitoring (APM) tools
  • Open Telemetry
  • Grafana
  • Prometheus
• Experience developing and maintaining highly available, resilient, and secure distributed systems.
• Proven ability to lead complex technical initiatives and influence organizational technology adoption.
• Experience establishing technical standards, governance frameworks, and engineering policies.
• Excellent communication, stakeholder engagement, and leadership skills.
• Demonstrated ability to balance hands‑on engineering responsibilities with leadership and team coordination duties.

• Experience supporting AI model serving and inference platforms.
• Experience integrating large language models (LLMs) and generative AI technologies into enterprise applications.
• Experience with AI orchestration and workflow frameworks, including Lang Chain or similar technologies.
• Knowledge of vector databases, embeddings, and semantic search technologies.
• Experience implementing Retrieval‑Augmented Generation (RAG) architectures.
• Experience with…