Senior DevOps/Platform Engineer III

Pacific Northwest National Laboratory•Seattle, OH

7h•Hybrid

About The Position

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. Join PNNL's AI engineering team and help architect the next generation of intelligent systems powering national security missions. As a Senior DevOps/Platform Engineer, you will design and build 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 experienced engineers who are ready to apply deep expertise in AI/ML infrastructure, distributed systems, and production software engineering while leading technical efforts, mentoring teammates, and helping shape the future of our 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: https://www.pnnl.gov/ai-and-data-analytics This position is based in Richland, WA or Seattle, WA and requires an onsite presence Monday through Thursday, with Friday as required by business needs.

Requirements

PhD and 1 year of Software Engineering experience -OR- MS/MA and 3 years of Software Engineering experience -OR- BS/BA and 5 years of Software Engineering experience -OR AA and 14 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 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.
Current, hands-on software development experience using Python.
U.S. Citizenship
Background Investigation: Applicants selected will be subject to a Federal background investigation and must meet eligibility requirements for access to classified matter in accordance with 10 CFR 710, Appendix B.
Drug Testing: All Security Clearance positions are Testing Designated Positions, which means that the applicant selected for hire is subject to pre-employment drug testing, and post-employment random drug testing. In addition, applicants must be able to demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).
Mandatory Requirements: Please be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.

Nice To Haves

Degree in computer science, software engineering, or related field.
3-5 years of hands-on DevOps, Platform Engineering, Site Reliability Engineering, or Infrastructure Engineering experience.
Expertise in Python, including active use for the past three years, and proficiency in at least one other language (C#/.NET, C++, or Go).
Demonstrated experience in Agentic AI to develop code and infrastructure.
Experience in contributing to technical direction and independently structure complex problems into actionable work, in collaboration with senior engineers and cross-functional teams.
Contributions to open-source infrastructure projects or active participation in DevOps communities.

Responsibilities

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.