Senior AI Systems Engineer

July 3, 2026 Auto Import

Essential Functions: <ul> <li>Lead the deployment, integration, and operational support of AI platforms, tools, and services, ensuring compatibility with existing systems and enterprise processes.</li> <li>Design, implement, monitor, and optimize AI infrastructure, working with server, cloud, and platform engineering teams.</li> <li>Operationalize machine learning workflows and support AI-enabled applications from development through production deployment and sustainment.</li> <li>Build and maintain CI/CD and MLOps pipelines for model packaging, testing, deployment, rollback, and lifecycle management.</li> <li>Implement infrastructure automation using scripting, Infrastructure as Code, and configuration management practices.</li> <li>Provide ongoing technical support, troubleshooting, root cause analysis, and documentation for AI platforms and user-facing AI services.</li> <li>Maintain observability across AI systems through logging, metrics, performance monitoring, alerting, and incident response practices.</li> <li>Ensure security, compliance, and governance requirements are met, including participation in audits, vulnerability management, and secure architecture reviews.</li> <li>Assess and implement system enhancements to improve performance, scalability, reliability, and cost efficiency.</li> <li>Collaborate across divisions to support diverse AI initiatives and align technical implementations with mission and business objectives.</li> <li>Evaluate emerging AI tools, frameworks, and infrastructure approaches for operational fit, supportability, and long-term value.</li> <li>Develop and maintain technical documentation, runbooks, architecture diagrams, and operational procedures.</li> </ul> Experience and Skills Required: <ul> <li>Bachelor’s degree in computer science, Engineering, Information Technology, or a related STEM field with 8-10 years of engineering experience. </li> <li>2+ years of experience supporting AI/ML platforms, MLOps workflows, model deployment, or AI-enabled infrastructure.</li> <li>Strong coding and automation skills in Python, Bash, or similar scripting languages.</li> <li>Experience with AI/ML frameworks and tooling such as PyTorch, Hugging Face, or similar ecosystems.</li> <li>Proficiency with DevOps and MLOps practices, including CI/CD pipelines, Git-based workflows, containerization, and Kubernetes.</li> <li>Experience deploying AI/ML models or AI services into operational environments, including containerized, cloud, or high-performance computing environments.</li> <li>Familiarity with security frameworks and compliance standards such as NIST and CMMC.</li> <li>Familiarity with AI security functionality in enterprise environments including OAuth</li> <li>Strong communication skills and the ability to collaborate effectively across technical and non-technical teams. </li> </ul> Preferred: <ul> <li>Advanced degree or certifications related to AI or machine learning.</li> <li>Experience integrating AI models into scientific workflows.</li> <li>Familiarity with large language model (LLM) APIs and orchestration frameworks such as OpenAI, Hugging Face, LangGraph, or LangChain.</li> <li>Experience with model serving, inference optimization, or AI platform tools such as MLflow, Kubeflow, vLLM, or similar.</li> <li>Experience with simulations for scientific or engineering projects, particularly physical systems simulations.</li> <li>Experience with GPU-based systems or running AI models in HPC environments.</li> <li>Experience writing and deploying MCP Servers on Kubernetes</li> <li>DoD experience</li> <li>Secret Security Clearance – Active or Inactive</li> </ul> Education: <ul> <li>Bachelor’s degree in CS, Software Engineering or other IT-related field or equivalent experience</li> </ul> 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.

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