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 model (LLM) APIs and orchestration frameworks such as OpenAI Hugging Face LangGraph or LangChain. Experience with model serving inference optimization or AI platform tools such as MLflow Kubeflow vLLM or similar. Experience with simulations for scientific or engineering projects particularly physical systems simulations. Experience with GPU-based systems or running AI models in HPC environments. Experience writing and deploying MCP Servers on Kubernetes DoD experience Secret Security Clearance – Active or Inactive Education Bachelor’s degree in CS Software Engineering or other IT-related field or equivalent experience REMOTE WORK NOTICE This position may be performed fully remote hybrid or onsite at an ARA office. Preference will be given to candidates located onsite in the Albuquerque NM and Raleigh NC area.