Senior Software Engineer III

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, 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.

Responsibilities

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.

Who You Are

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. You excel at translating technical requirements into working solutions, selecting appropriate approaches for challenging problems, and contributing meaningfully to technical direction and project success.

What You'll Build

AI Systems & Platforms

• Develop and deploy agentic AI systems with reasoning and decision-making capabilities
• Build components of LLM orchestration frameworks using LangChain, LlamaIndex, 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

Scalable Infrastructure & Data Systems

• 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

Mission-Critical Production Systems

• 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

Technical Leadership

• 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

Technical Knowledge, Skills, and Abilities

Core Engineering Excellence

• Demonstrated proficiency in Python and working knowledge of at least one additional language (Java, C#/.NET, Go, C++, 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 DevOps 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 while consistently leveraging AI assist tools (e.g., GitHub Copilot, Claude, Cursor) to accelerate development, generate test cases, and enhance problem-solving throughout the software development lifecycle

AI/ML & Deep Learning