Hiring Event - Chief Software Engineer V

Pacific Northwest National Laboratory•Richland, WA

1d•Onsite

About The Position

The AI and Data Analytics Division, part of the National Security Directorate (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. This role is performed full-time onsite at the PNNL campus in Richland, WA or Seattle, WA.

Requirements

PhD and 5 years of relevant experience -OR- MS/MA and 7 years of relevant experience -OR- BS/BA and 9 years of relevant experience -OR- AA and 18 years of relevant experience -OR- HS/GED and 20 years of relevant experience.
Relevant experience is defined as 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.
Ability 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).

Nice To Haves

Strong Python expertise
Significant experience in DevOps, platform engineering, site reliability engineering, distributed systems, telemetry and observability, security, and automated software delivery.
Experience designing and deploying agentic AI systems and large-scale data platforms in real-world environments.
Expertise includes large language models, retrieval-augmented generation, multi-step reasoning, autonomous decision workflows, model and data orchestration, production-quality AI systems, and designing and operating petabyte-scale ETL/ELT pipelines.

Responsibilities

Design and build scalable AI platforms, cloud-native infrastructure, containerized environments (Docker/Kubernetes), CI/CD pipelines, IaC, real-time data stream architectures, and reliable, secure production systems.
Push the boundaries of agentic AI systems characterized by autonomy, adaptability, reasoning, collaboration, and effective tool use.
Design and deploy agentic AI systems and large-scale data platforms in real-world environments.
Shape research directions, lead multidisciplinary R&D programs, develop external partnerships, and mentor AI scientists and engineers.