DevOps/Platform Engineer II

Pacific Northwest National Laboratory•Richland, WA

59d•Onsite

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, Integrated Discovery 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 the National Security Directorate, 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 build the next generation of intelligent systems powering national security missions. As a DevOps/Platform Engineer, you'll develop scalable AI platforms, cloud-native infrastructure, and high-performance data pipelines that enable advanced machine learning and real-time intelligence solutions. This role is ideal for early- to mid-career engineers looking to expand their expertise in AI/ML infrastructure, cloud technologies, and distributed systems while working alongside leading researchers and engineers.

Requirements

PhD -OR- MS/MA -OR- BS/BA and two (2) years of professional software development experience
Current, hands-on software development experience using Python
U.S. Citizenship
Ability to obtain and maintain a federal security clearance.
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).
The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication.
All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation).
Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment.
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.

Nice To Haves

Degree in computer science, software engineering, or related technical field.
Experience with cloud platforms, infrastructure automation, or CI/CD through professional, academic, or personal projects.
Programming or scripting experience using Python, Bash, or similar languages.
Familiarity with containerization technologies (e.g., Docker) and an interest in Kubernetes and cloud-native technologies.
Exposure to AI/ML workflows, data pipelines, or model deployment through professional, academic, or personal projects.

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.
Improve system performance, observability, security, and operational reliability across production environments.
Collaborate with software engineers, data scientists, and researchers to deliver innovative AI capabilities.
Participate in architecture discussions, code reviews, technical planning, and continuous improvement while growing your technical leadership.