Senior Software Engineer III

Overview

At PNNL, our core capabilities are divided among major departments referred to as directorates. These directorates focus on specific areas of scientific research or other functions, each 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 the 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 tackle complex, real‑world threats to our nation and the world.

The AI and Data Analytics Division, part of NSD, combines domain expertise and creative integration of advanced hardware and software to deliver computational solutions that address complex data and analytics challenges.

We are seeking a Senior Software Engineer to join PNNL’s advanced AI engineering initiatives, contributing to next‑generation systems spanning agentic AI platforms, large‑scale data orchestration, and real‑time intelligence processing. In this role, you'll apply your expertise in scalable system design and AI/ML engineering to build mission‑critical capabilities while developing your technical leadership and establishing yourself as a key contributor to our engineering community.

You're an accomplished engineer with strong foundations in scalable system design, AI/ML development, and production software engineering. You're ready to take on increasing technical responsibility, leading components of complex systems while mentoring junior team members.

• Develop and deploy agentic AI systems with reasoning and decision‑making capabilities
• Build components of LLM orchestration frameworks using Lang Chain, Llama Index, and emerging platforms
• Contribute to MLOps platforms including experiment tracking, model versioning, and deployment pipelines
• Create developer tooling, utilities, and interfaces for AI‑native frameworks
• Integrate multi‑modal data sources into cohesive processing pipelines

• Develop microservices within distributed architectures handling high‑throughput workloads
• Build components of real‑time streaming platforms and event‑driven systems
• Implement data pipelines for large‑scale ETL, data processing, and analytics
• Deploy containerized applications using Kubernetes and support CI/CD pipelines
• Contribute to systems deployed in secure and edge environments

• Deploy AI systems with appropriate monitoring, logging, and observability
• Ensure code quality, security best practices, and compliance standards
• Build geospatial processing, time‑series, and data fusion capabilities
• Support system performance optimization and troubleshooting

• Lead technical components of projects and tasks
• Mentor junior staff and contribute to team knowledge sharing
• Participate in design discussions and contribute to architectural decisions
• Support proposal development with technical content and scoping
• Build effective collaborations across teams and S&E domains

• Demonstrated proficiency in Python and working knowledge of at least one additional language (Java, C#/.NET, C++, Go, Rust) with deep knowledge of software engineering principles including object‑oriented design, design patterns, data structures, algorithms, and clean code practices
• Proficiency with version control systems (Git), collaborative development workflows, and strong foundation in automated testing methodologies including unit testing, integration testing, end‑to‑end testing, and test‑driven development (TDD)
• Understanding of CI/CD pipelines and Dev Ops practices with ability to contribute to build automation, deployment processes, and release management while writing maintainable, well‑documented, and performant code
• Ability to lead technical discussions around system design, microservice architecture, and distributed computing patterns…