Lead Backend Software Engineer IV; Seattle, WA

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.

We are seeking a Lead Software Engineer to join PNNL's advanced AI engineering initiatives—spanning agentic AI architectures, petabyte-scale data orchestration, and real-time multi-intelligence processing—that are defining the future of national security technology. With your expertise in scalable system design, AI/ML engineering, and complex data architectures, you'll contribute to revolutionary capabilities that process multi-modal intelligence data at unprecedented scale and speed. We operate with startup agility and urgency, rapidly iterating and deploying solutions where failure isn't an option.

As a Lead Software Engineer on PNNL's Software Engineering and Architectures (SEA) team, you will architect and lead the development of mission-critical AI systems, design systems at scale in support of mission objectives, and drive technical strategy for some of the nation's most sophisticated intelligence and security applications. You'll take ownership from concept to deployment, mentor and develop staff, collaborate with research scientists and domain experts, and translate cutting-edge research into production-ready systems deployed in highly secure environments—all while maintaining the entrepreneurial mindset that turns breakthrough research into operational reality.

What You'll Architect & Build:

• Software Platforms – Design scalable microservices architectures that coordinate across multiple domains, build robust API gateways for classified environments, architect service mesh implementations that handle the nation's most sensitive traffic
• High-Performance Processing Systems – Lead distributed system design processing data from hundreds of sources simultaneously, architect real-time streaming platforms that handle terabytes per hour, design event-driven architectures that scale horizontally across data centers
• Mission-Critical Infrastructure – Design container orchestration platforms that span multiple security domains, architect CI/CD pipelines processing millions of deployments, build monitoring and observability systems across secure enclaves
• Technical Leadership with Impact – Mentor engineering teams building systems that push the boundaries of software architecture, drive technical decisions that influence platform strategy, lead cross-functional initiatives spanning multiple development teams

Technical Expertise Expected:

• Programming Excellence – Fluency in Python, with proficiency in C#/.Net, Go, JavaScript/Type Script, Java, C/C++, Rust
• Cloud & Infrastructure – AWS/Azure architecture, Kubernetes orchestration, Infrastructure as Code, GCP, Multi-cloud, Edge computing
• Data & Storage – S3, Elasticsearch/Open Search, Postgre
  
  SQL, Mongo
  
  DB, Redshift, Delta Lake, Vector stores
• AI/ML Engineering – Agentic AI systems, LLMs, model deployment & orchestration, MLOps platforms, distributed training, model serving at scale, vector databases, graph analytics
• Intelligence…