Early Career R&D Agentic AI Systems Engineer, Onsite

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Sandia National Laboratories is the nation’s premier science and engineering lab for national security and technology innovation, with teams of specialists focused on cutting-edge work in a broad array of areas. Some of the main reasons we love our jobs:

Challenging work with amazing impact that contributes to security, peace, and freedom worldwide

Extraordinary co-workers

Some of the best tools, equipment, and research facilities in the world

Career advancement and enrichment opportunities

Flexible work arrangements for many positions include 9/80 (work 80 hours every two weeks, with every other Friday off) and 4/10 (work 4 ten-hour days each week) compressed workweeks, part-time work, and telecommuting (a mix of onsite work and working from home)

Generous vacation, strong medical and other benefits, competitive 401k, learning opportunities, relocation assistance and amenities aimed at creating a solid work/life balance*

World-changing technologies. Life-changing careers. Learn more about Sandia at: http://(Use the "Apply for this Job" box below)..gov

* These benefits vary by job classification.

What Your Job Will Be Like:

We are seeking a R&D S&E Artificial Intelligence Engineer to provide systems engineering for Agentic AI systems. On any given day, you may be called on to partner with a cross-functional team to:

Design, develop, and optimize agent and multi-agent AI tooling and workflows against technical goals, domain context and operating environment, and success metrics.

Define and apply an agentic system's development lifecycle, including requirements, analysis, architecture design, model and agent selection, tool integration, testing, deployment, and continuous improvement.

Work with researchers in other sciences at the lab (e.g., statisticians, mathematicians, computer scientists, etc.) to develop evaluation frameworks to measure and communicate system reliability, trustworthiness, safety, accuracy, and national security impact.

Build automated evaluation and regression-testing pipelines for prompts, tools, models, workflows, and emergent agent behaviors.

Integrate agent capabilities with tools, APIs, orchestration frameworks, and agent architectures.

Establish and operate LLMOps/Agent Ops practices including CI/CD, automated testing, monitoring, telemetry, cost tracking, and incident response for AI agents in production.

Deploy and scale agent AI capabilities across the laboratory and customer implementations.

Continuously evaluate new models, frameworks, architectures, and methodologies, and translate relevant advances to improve system quality and performance.

Work with human systems integration teams to ensure efficacy of overall agentic system; assess human-agent team performance, including whether users can effectively understand, supervise, collaborate with, and accomplish their work through the system.

Due to the nature of the work, the selected applicant will be required to work onsite. Relocation can be provided for those that qualify.

Salary Range:

$102,400 - $199,700

* Salary range is estimated, and actual salary will be determined after consideration of the selected candidate's experience and qualifications, and application of any approved geographic salary differential.

Qualifications We Require:

A Bachelor's degree in a relevant discipline, or an equivalent combination of directly relevant education and engineering or scientific experience that demonstrates the knowledge, skills, and ability to perform independent research and development.

Ability to obtain and maintain a DOE Q and SCI clearance.

Qualifications We Desire:

The ideal R&D Artificial Intelligence candidate for Sandia National Laboratories will in addition possess the following:

Graduate degree in a relevant computationally-intensive discipline where an independent research project was a graduation requirement (e.g., independent project, thesis, or dissertation).

Experience in developing software and AI systems for enterprise and national security applications.

Demonstrated software development skills and familiarity with modern software development practices.

Proven ability to work and communicate effectively in a collaborative and interdisciplinary team environment.

Also, for this posting we are seeking individuals with the following experience:

Working understanding of generative AI methods such as diffusion models, large language models (LLMs), or Variational Autoencoders (VAEs).

Solid understanding of LLM mechanics: context windows, tokenization, prompt engineering.

Strong software engineering fundamentals: e.g., Python, API design, async programming, testing/debugging distributed systems.

Familiarity with tool-use/function-calling patterns - how models decide when and how to invoke external tools.

Knowledge of orchestration frameworks (Lang Chain, Lang Graph, Auto Gen, CrewAI, or building custom orchestration).

Tool/function schema…