Senior AI Systems Engineer

Essential Functions

• Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.
• Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.
• Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.
• Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.
• Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.
• Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.
• Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.
• Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.
• Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.
• Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.
• Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.
• Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.

Experience and Skills Required

• Bachelor’s degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience.
• 2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.
• Strong coding and automation skills in Python, Bash, or...