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 Dev Ops 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, Lang Graph, or Lang Chain.

* 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.