Senior Software Engineer, Agentic AI

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget. Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have an Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.

The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex, real-world threats to our nation and the world. The AI and Data Analytics Division, part of NSD, consists of over 400 staff and combines profound domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering to operations, providing the tools to innovate quickly and field results faster.

Our strengths are integrated across the data analytics lifecycle, from data acquisition and management to analysis and decision support.

We are seeking an experienced Senior Software Engineer to drive the design, development, execution, and integration of groundbreaking agentic AI agents. This role is perfect for engineers passionate about building tools for other developers, working across diverse technology stacks, and shaping the future of AI enablement in production environments.

This role is unique. It isn't just about building AI agents and working with agentic frameworks. We're looking for someone with a deep understanding of what it takes to build highly scalable systems from scratch, pulling on experience in IaC, Dev Ops, MLOps, Data Engineering and more. We want someone who consistently seeks out and employs new technology on increasingly complex problems, and can transform those complex problems into tractable solutions.

A coder, designer, architect, leader and engineer with a penchant for working closely with data scientists and wrangling and submitting data to large-scale AI and ML implementations.

You will partner with cross-functional teams to advance developer tooling, enhance agent authentication and orchestration frameworks, and create impactful real-world demos.

Responsibilities Include:

• Design and deploy scalable AI systems capable of dynamic reasoning and actionable decision-making
• Build and optimize infrastructure, leveraging containerization tools and automated CI/CD pipelines for efficient AI deployment
• Develop and manage robust data pipelines for sourcing, preprocessing, and experimentation
• Monitor system performance, troubleshoot issues, and ensure compliance with ethical AI standards
• Collaborate across engineering, product, and security teams to align systems with organizational goals and industry regulations
• Create developer-focused tooling and maintain high-quality documentation, including API references, quick starts, and best practices for AI-native frameworks
• Lead the integration of emerging AI frameworks by developing adapters, utilities, interfaces, and orchestration layers
• Contribute to engineering standards by driving design discussions and shaping team-wide architectural decisions
• Ensure resilience and security in agent-to-agent and model-to-service communications
• Mentor and guide junior scientists and engineers while fostering a collaborative team environment

This position is onsite and requires onsite work in either Richland, WA or Seattle, WA.

Minimum Qualifications:

• PhD and 3 years of relevant experience
  -OR-
• MS/MA or higher and 5 years of relevant experience
  -OR-
• BS/BA and 7 years of relevant experience
  -OR-
• AA and 16 years of relevant experience
  -OR-
• HS/GED and 18 years of relevant experience
• Qualifying software development experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development may be counted

Preferred Qualifications:

• Demonstrated expertise in designing and deploying agentic AI systems in real-world applications.
• Experience engaging with funding agencies such as the Department of Energy, National Nuclear Security Administration, Department of Defense, or Department of Homeland Security, and demonstrated ability to initiate substantial new R&D efforts and collaborations.
• Demonstrated experience in applying AI to scientific challenges, such as solving problems in energy systems, climate modeling, materials design, or molecular science.
• Expert-level software engineering:
  Git-based workflows, code reviews, automated testing, CI/CD pipelines, static analysis, thorough documentation, secure coding practices, performance profiling, and Agile/Dev Ops methodologies.
• Cloud-native system design: API and microservice architecture,…