Senior AI Systems Engineer

This is a fully remote position, open to applicants in New Mexico, +1 more state.

📋 Description

• Lead the implementation, integration, and operational maintenance of AI platforms, tools, and services, ensuring they are compatible with current systems and enterprise processes.

• Design, execute, monitor, and enhance AI infrastructure in collaboration with server, cloud, and platform engineering teams.

• Operationalize machine learning workflows and provide support for AI-driven applications from development to production deployment and ongoing maintenance.

• Develop and sustain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.

• Utilize scripting, Infrastructure as Code, and configuration management practices to automate infrastructure.

• Deliver continuous technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.

• Maintain observability of AI systems through logging, metrics, performance monitoring, alerting, and incident response protocols.

• Ensure adherence to security, compliance, and governance standards, including engagement in audits, vulnerability management, and secure architecture evaluations.

• Evaluate and implement system improvements to enhance performance, scalability, reliability, and cost-effectiveness.

• Collaborate across departments to support various AI projects and align technical implementations with organizational goals and objectives.

• Assess new AI tools, frameworks, and infrastructure strategies for operational viability, supportability, and long-term benefits.

• Create and update technical documentation, runbooks, architecture diagrams, and operational procedures.

⛳️ Requirements

• Bachelor’s degree in computer science, engineering, information technology, or a related STEM discipline with 8-10 years of engineering experience.

• Over 2 years of experience in supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.

• Proficient coding and automation skills in languages such as Python, Bash, or other similar scripting languages.

• Experience with AI/ML frameworks and tools like PyTorch, Hugging Face, or comparable ecosystems.

• Expertise in DevOps and MLOps methodologies, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.

• Proven experience in deploying AI/ML models or AI services in operational settings, including containerized, cloud, or high-performance computing environments.

• Knowledge of security frameworks and compliance standards such as NIST and CMMC.

• Understanding of AI security functionalities in enterprise environments, including OAuth.

• Excellent communication skills with the ability to collaborate effectively across both technical and non-technical teams.

🏝️ Benefits

• Health insurance

• Retirement plans

• Paid time off

• Flexible work arrangements

• Professional development

• Security clearance support