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 similar scripting languages.


* Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems.


* Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.


* Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments.


* Familiarity with security frameworks and compliance standards such as NIST and CMMC.


* Familiarity with AI security functionality in enterprise environments including OAuth


* Strong communication skills and the ability to collaborate effectively across technical and non-technical teams.

Preferred:


* Advanced degree or certifications related to AI or machine learning.


* Experience integrating AI models into scientific workflows.


* Familiarity with large language mode...