Lead DevOps/Platform Engineer IV

Pacific Northwest National Laboratory•Seattle, OH

3d•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 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.

Requirements

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.
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).
Applicants will be considered ineligible for security clearance processing by the U.S. Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.
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.
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.
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 production deployment, operational handoff, and continuous improvement.

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.