Hiring Event - Lead Software Engineer IV

Pacific Northwest National Laboratory•Richland, WA

1d•Onsite

About The Position

The National Security Directorate (NSD) at PNNL drives science-based, mission-focused solutions to address complex, real-world threats. Within NSD, the AI and Data Analytics Division combines domain expertise with advanced hardware and software to deliver computational solutions for complex data and analytic challenges. This division works in multidisciplinary teams, connecting foundational research to engineering and operations, providing tools to innovate quickly and field results faster. Their strengths span the entire data analytics lifecycle, from acquisition and management to analysis and decision support. This role offers opportunities to advance cutting-edge research and build solutions for critical national security missions, working within a team of over 400 data scientists, software engineers, mathematicians, and human-centered computing researchers.

Requirements

PhD and 3 years of relevant experience -OR- MS/MA and 5 years of relevant experience -OR- BS/BA and 7 years of relevant experience -OR- AA and 16 years of relevant experience -OR- HS/GED and 18 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 pass a Federal background investigation.
Ability to pass pre-employment and random drug testing for illegal drugs, including marijuana, and demonstrate non-use 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.
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.