Academic Graduate Appointee

LLNL•Livermore, CA

8h•$10,215

About The Position

Lawrence Livermore National Laboratory (LLNL) is seeking an Academic Graduate Appointee to join the Data Science and Analytics group in the Computing organization. The successful candidate will be responsible for designing, building, testing, and improving practical AI-enabled tools and agentic solutions, from concept to high-fidelity prototype. This role may involve focus areas such as AI application development, platform engineering, model evaluation, data integration, and developer tooling.

Requirements

Must be eligible to access the Laboratory in compliance with Section 3112 of the National Defense Authorization Act (NDAA).
Bachelor's or Master’s degree in computer science, software engineering, data science, artificial intelligence, machine learning, or a related field.
Software engineering experience with languages such as Python or TypeScript and practical experience using AI-assisted development tools.
Experience building applications with large language models, machine learning services, or generative AI APIs.
Familiarity with agent frameworks, tool calling, retrieval-augmented generation, embeddings, prompt engineering, structured outputs, and multi-step workflows.
Experience designing APIs, data pipelines, distributed systems, or asynchronous workflows and integrating with internal systems, APIs, databases, or third-party services.
Ability to rapidly evaluate new technologies, debug complex issues across models, prompts, application code, data, and infrastructure, and make pragmatic architectural decisions.
Clear written and verbal communication skills, ability to work effectively across technical and non-technical teams, and a product-oriented focus on useful, trustworthy, and maintainable solutions.

Responsibilities

Conduct research in assigned area under general direction and supervision.
Design, build, test, and improve practical AI-enabled tools and agentic solutions, moving quickly from ideas to working prototypes and reliable high-fidelity prototypes.
Rapidly prototype AI-powered applications, agents, and workflows for high-value use cases.
Build reusable platform components for model access, agent orchestration, tool use, data integration, and evaluation.
Integrate large language models with internal systems, APIs, databases, and third-party services, including solutions that use tool calling, and multi-step workflows.
Evaluate models, frameworks, and infrastructure based on quality, reliability, latency, security, and cost.
Deploy and operate AI services using modern cloud, container, and CI/CD practices while establishing appropriate controls for privacy, security, permissions, and responsible AI use.
Use AI-assisted coding, research, and automation tools to accelerate development and document technical decisions, experiments, platform capabilities, and best practices.
Collaborate with product, engineering, design, and business teams to identify valuable AI use cases.
Perform other duties as assigned.