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ARA

Innovative Solutions to Complex Problems

Senior AI Systems Engineer

AI EngineerMachine Learning EngineerFull TimeRemoteSeniorTeam 1,001-5,000H1B No SponsorCompany SiteLinkedIn

Location

United States

Posted

4 days ago

Salary

0

Seniority

Senior

No structured requirement data.

Job Description

Senior AI Systems Engineer

ARA

Role Description - 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. Qualifications - 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. Requirements - 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. Benefits - 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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