Overview
At PNNL,our core capabilities are dividedamongmajor departmentsthat werefer to asDirectorateswithin the Lab,focused on a specific area of scientific research orother function, with its own leadership teamand dedicated budget.
Our Science & TechnologydirectoratesincludeNational Security,Earthand Biological Sciences, Physical and Computational Sciences, andEnergy andEnvironment.In addition,we have anEnvironmental Molecular Sciences Laboratory,a Department of Energy, Office of Science user facilityhoused on the PNNL campus.
The National Security Directorate (NSD) drives science-based, mission-focused solutions to take on complex,real-worldthreats 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
Join PNNL's AI engineering team and help lead the development of the next generation of intelligent systems powering national security missions. As a Lead DevOps/Platform Engineer , you will architect and deliver scalable AI platforms, cloud-native infrastructure, and large-scale data orchestration capabilities that enable advanced machine learning, agentic AI, and real-time intelligence solutions. This role is ideal for accomplished engineers who are ready to provide technical leadership across complex systems, guide architectural and engineering decisions, mentor and develop teammates, and help shape the technical direction and future of our AI engineering capabilities.
What You'll Build
- Build and deploy cloud-native AI platforms, agentic AI applications, and large language model (LLM) solutions.
- Develop scalable data pipelines, streaming architectures, APIs, and microservices to process high-volume, real-time data.
- Design and maintain containerized infrastructure, CI/CD pipelines, and automated testing to support reliable software delivery.
- Drive system performance improvements, observability, security, and operational reliability across production environments.
- Lead software engineers, data scientists, and researchers to deliver innovative AI capabilities.
- Lead architectural discussions, set direction for code reviews and engineering best practices and drive continuous improvement throughout the team.
National Interest Project Examples
- Detect and prevent smuggling of drugs and contraband at ports of entry (Link)
- Develop large data pipelines to thwart funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders (Link)
- Applying big data solutions to national security problems (Link)
- Applying image classification for nuclear forensics analysis (Link)
- Develop capabilities for scalable geospatial analytics (Link)
Read more about AI and Data Analytics division:
This position is based in Seattle, WA, or Richland, WA, and requires an onsite presence Monday through Thursday, with Friday as required by business needs.
Qualifications
Minimum Qualifications:
- PhD and 3 years of Software Engineering experience -OR-
- MS/MA and 5 years of Software Engineering experience -OR-
- BS/BA and 7 years of Software Engineering experience -OR-
- AA and 16 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development -OR-
- HS/GED and 18 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development.
- Current, hands-on software development experience using Python.
Preferred Qualifications:
- Degree in computer science, software engineering, or related field.
- Expertise in Python, including active use for the past five years, and proficiency in at least one other language (Go, C#, Rust).
- Expertise in leveraging Agentic AI to develop code and build/maintain infrastructure and systems.
- Track record of architecting and operating large-scale infrastructure supporting significant user bases, high-volume transaction systems, petabyte-scale data platforms, or production ML systems serving millions of predictions.
- Experience building and leading high-performing platform engineering, DevOps, or MLOps teams through hiring, mentoring, technical guidance, and career development.
- Experience establishing infrastructure practices, platform strategies, MLOps frameworks, and DevOps transformation initiatives on an organizational scale.
- Background in mission-critical, regulated, or high-security environments (government, defense, financial services, healthcare) with understanding of compliance requirements for both traditional systems and ML/AI applications.
- Demonstrated success leading complex, multi-team infrastructure and MLOps initiatives from architecture through