Senior AI Systems Engineer

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.

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

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.