Senior AI Systems Engineer at ARA

United States

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.