AI Solutions Engineer

Company Description

Join us and make YOUR mark on the World!

Lawrence Livermore National Laboratory (LLNL) has turned bold ideas into world-changing impact advancing science and technology to strengthen U.S. security and promote global stability.

Our mission spans four critical national security areas nuclear deterrence, threat preparedness, energy security, and multi-domain defense empowering teams to take on the toughest challenges of today and tomorrow. With a culture built on innovation and operational excellence, LLNL is a place where your expertise can make a real impact.

We have an opening for an AI Solutions Engineer with robust expertise in enhancing business applications with AI capabilities and leveraging Retrieval Augmented Generation (RAG) technologies. In this role, you will help design, develop, and deploy solutions that integrate AI technologies across our business systems application portfolio. You will work closely with application developers, data scientists, product owners, and business analysts to determine how best to AI enable our business applications.

This position is in the Enterprise Application Services (EAS) Division which is part of the Computing Directorate, in support of the LivIT Program.

This position offers a hybrid schedule, blending in-person and virtual presence. You will have the flexibility to work from home one or more days per week.

• Conduct and maintain Retrieval Augmented Generation (RAG) data pipelines by integrating LLMs (for example, OpenAI, Anthropic, etc.) with enterprise document stores and vector databases.
• Collaborate in the development of scalable, secure APIs, microservices, and MCP servers that enable RAG based application access to business system data sources.
• Partner with application development teams to optimize retrieval performance, improve accuracy through prompt engineering and grounding techniques, and reduce LLM token usage to help manage AI related costs.
• Collaborate with data engineering teams to integrate virtualized data sources into AI workflows.
• Build connectors and middleware to access and transform real time operational data for consumption by LLMs and analytics services.
• Partner with application developers and stakeholders across operational areas such as Finance, HR, and Procurement to help identify opportunities to leverage AI tools that reduce manual workflows.
• Monitor AI technology performance and provide solutions to improve usability, explainability, and relevance.
• Perform other duties as assigned.

• Ability to obtain and maintain a U.S. DOE L level security clearance in the future, which requires U.S. citizenship.
• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related technical field.
• Significant experience in leveraging business operations data to support AI RAG efforts.
• Significant experience building AI powered applications, particularly with leveraging RAG services, vector databases, and LLM APIs.
• Significant experience in implementing RESTful APIs, microservices, MCP servers, or cloud platform services.
• Advanced skills in programming languages such as Python, JavaScript/Type Script, or Java.
• Advanced knowledge of prompt tuning, feedback loops, and implementing guardrails/safeguards in AI systems design.
• Advanced verbal and written communication skills necessary to effectively collaborate in a team environment and present and explain technical information and provide advice to management.

• Experience working within Agile/Scrum environments supporting cross functional development teams.
• Exposure to vector embeddings, semantic search, and knowledge graph technologies.
• Familiarity with Dev Ops, CI/CD pipelines, and containerization.

$175,530 - $222,564 Annually. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting; pay will not be below any applicable local minimum wage. An employee's position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills,…