DevOps/Platform Engineer II

Pacific Northwest National Laboratory•Richland, WA

6d•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, 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 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

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.