AI (Artificial Intelligence) Infrastructure Architect

LLNL•Livermore, CA

2d•$175,530 - $267,060•Hybrid

About The Position

We have an opening for an AI (Artificial Intelligence) Infrastructure Architect to design, implement, and support Enterprise AI initiatives that support the Laboratory. You will work as part of a small, collaborative team responsible for AI infrastructure focused initiatives that will benefit LivIT and the entire Lab. You will collaborate with AI Engineers, Developers, IT Infrastructure and leadership across LivIT and our programmatic customers to drive strategic AI efforts that support innovative needs and operational efficiencies. This position offers the opportunity to work in a dynamic and highly technical environment, supporting critical infrastructure for enterprise-level applications. This position is in the Enterprise Infrastructure Services (EIS) Division within the Computing Directorate and in support of the LivIT Systems Networks & Technologies Program Area. This position will be filled at either the SES.3 or SES.4 level based on knowledge and related experience as assessed by the hiring team. Additional job responsibilities (outlined below) will be assigned if hired at the higher level. Depending on your assignment, this position may offer a hybrid schedule, blending in-person and virtual presence. You may have the flexibility to work from home one or more days per week.

Requirements

Ability to obtain and maintain a US DOE Q-level security clearance which requires U.S. Citizenship.
Bachelor’s degree in Computer Science, Software Engineering, Management Information Systems, or a related field, or an equivalent combination of education and relevant experience.
Significant experience in Python, R, or other programming languages commonly used in AI development, with a strong understanding of scripting for automation and operational workflows.
Advanced experience with NLP tools and techniques for automating tasks such as ticket triage, sentiment analysis, or chatbots, with proficiency in libraries such as SpaCy, NLTK, or Hugging Face.
Hands-on experience with at least three AI or GenAI tools and frameworks, such as OpenAI, Anthropic, Co-Pilot, Amazon Q, Hugging Face, TensorFlow, PyTorch, Bedrock, RAG solutions, or similar technologies.
Significant experience with at least two automation tools, frameworks, or Infrastructure-as-Code (IaC) platforms, including Ansible, Terraform, Kubernetes, Puppet, Jenkins, or comparable solutions.
Extensive experience in systems programming to develop, configure, monitor, and automate web applications, cloud services, containers, and COTS infrastructures to ensure high availability and robust security.
Proven ability to collaborate effectively with customers, IT teams, developers, database administrators, systems administrators, and security professionals to design and deliver containerized infrastructures and services tailored to business objectives.
Advanced verbal and written communication skills necessary for preparing and delivering presentations, articulating findings and recommendations, and influencing management decisions using data-driven insights.

Nice To Haves

Expert knowledge of Infrastructure-As-Code (IaC) and CI/CD workflow pipelines to help support GenAI infrastructure modernization efforts.
Expert knowledge of APIs, microservices, and cloud platforms (e.g., AWS, Azure, Google Cloud).
Highly advanced knowledge of IT Infrastructure, including networks, servers, cloud platforms, and IT Service Management (ITSM) tools.
Significant hands-on experience building, managing, and scaling data lakes.

Responsibilities

Analyze operational inefficiencies and propose AI-driven solutions.
Leverage expertise in automation to optimize workflows, monitoring, and configuration management for AI frameworks, tools, and platforms.
Develop robust AI pipelines and infrastructure that align with organizational goals and business requirements.
Ensure AI related infrastructure efforts comply with security policy, collaborating with our Cyber Security Program.
Evaluate and integrate emerging AI technologies and tools in support of infrastructure initiatives, such as MLOps platforms, model optimization frameworks, and other AI services, to enhance infrastructure capabilities.
Monitor and analyze AI infrastructure performance, identify bottlenecks, and implement solutions to ensure scalability, reliability, and cost efficiency.
Perform other duties as assigned.
Oversee and lead the lifecycle of AI systems architectures, including requirements gathering, capacity planning, design, development, testing, documentation, implementation, upgrades, and performance optimization.
Serve as a mentor to and share knowledge with team members to enhance AI skills and abilities across the organization.