DevOps/Platform Engineer II - Richland, WA

We are seeking a DevOps/Platform Engineer to join PNNL's AI engineering team, contributing to innovative systems spanning agentic AI platforms, large-scale data orchestration, and real-time intelligence processing. This is an excellent opportunity for early to mid-career developers to apply their software engineering skills to meaningful national security challenges while growing their expertise in AI/ML systems, cloud infrastructure, and distributed computing.

Who You Are

You're a motivated software engineer with foundational experience in building production systems and a strong desire to grow your expertise in AI/ML and scalable infrastructure. You're comfortable working both independently on defined tasks and collaboratively on larger initiatives. You're eager to learn new technologies, apply software engineering best practices, and contribute to mission-critical systems while building your professional network and technical reputation.

What You'll Build

AI Systems & Platforms

• Develop components of agentic AI systems and LLM-based applications
• Implement features using frameworks like LangChain, LlamaIndex, or similar tools
• Build and maintain ML pipelines, data preprocessing workflows, and model deployment infrastructure
• Create utilities and tools that support AI/ML development and operations
• Work with multi-modal data including text, structured data, and sensor information

Data Pipelines & Infrastructure

• Build data pipelines for large-scale ETL, transformation, and analytics workflows
• Implement streaming data processors and event-driven components
• Develop microservices and APIs within distributed architectures handling high-throughput workloads
• Deploy containerized applications using Docker and Kubernetes
• Contribute to CI/CD pipelines and automated testing frameworks

Mission-Critical Production Systems

• Write clean, well-tested code following established best practices
• Implement monitoring, logging, and observability for applications
• Build developer tooling and documentation to support team productivity
• Contribute to system performance optimization and debugging efforts
• Support deployments in cloud and secure environments

Technical Leadership

• Work on small tasks and project elements, progressing to independent ownership
• Collaborate with cross-functional teams including data scientists, researchers, and senior engineers
• Participate in code reviews, design discussions, and technical planning
• Mentor junior staff and students when opportunities arise
• Contribute technical content to proposals and project documentation
• Present your work at team meetings and technical forums, * Detect and prevent smuggling of drugs and contraband at ports of entry [Link (https://www.pnnl.gov/sites/default/files/media/file/NII%20Capabilities%20072621_0.pdf) ]
• Develop large data pipelines to thwart funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders [Link (https://www.pnnl.gov/sites/default/files/media/file/PNNL_Treasury_AWS%20collab%201121.pdf) ]
• Applying big data solutions to national security problems [Link (https://www.pnnl.gov/news-media/science-front-line-ralph-perko) ]
• Applying image classification for nuclear forensics analysis [Link (https://www.pnnl.gov/sites/default/files/media/file/NSD_1259_FLYER_SharkzorHighlights_FINAL_0.pdf) ]
• Develop capabilities for scalable geospatial analytics [Link (https://www.pnnl.gov/sites/default/files/media/file/GeoBOSS%20Open-Source%20Geospatial%20Analytics%20at%20Scale.pdf) ]

This position is based in Richland, WA and requires an onsite presence Monday through Thursday, with Friday as required by business needs.

Infrastructure & Automation Fundamentals

• Working proficiency in Python with foundational knowledge of at least one additional language (Bash, Go, C#, JavaScript/TypeScript) for scripting and automation tasks
• Understanding of Infrastructure as Code principles with exposure to tools like Terraform, CloudFormation, or Ansible and ability to write basic infrastructure configurations
• Familiarity with version control workflows (Git) including branching, commits, pull requests, and collaborative development practices with willingness to learn CI/CD pipeline concepts and contribute to build automation
• Eagerness to learn and apply AI assist tools (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate learning, generate infrastructure code, troubleshoot issues, and improve automation script quality

MLOps & Machine Learning Infrastructure

• Foundational knowledge of machine learning concepts including model training, evaluation, and deployment with exposure to frameworks (PyTorch, TensorFlow, scikit-learn)
• Basic understanding of the ML lifecycle and MLOps principles including experiment tracking, model versioning, and monitoring with willingness to learn tools like MLflow, Weights & Biases, or Kubeflow
• Exposure to or willingness to learn about ML model serving, inference APIs, and supporting infrastructure for training and deployment pipelines
• Interest in supporting LLM applications, agent-based frameworks, and ML workloads on cloud platforms or Kubernetes with eagerness to grow expertise through hands-on projects

Cloud Platforms & Container Technologies

• Basic knowledge of cloud computing principles and familiarity with services within AWS, Azure, or GCP (compute, storage, networking, IAM)
• Exposure to containerization with Docker and foundational understanding of container orchestration concepts (Kubernetes) with willingness to learn pod management, deployments, and services
• Understanding of basic networking concepts including DNS, load balancing, and firewalls with awareness of RESTful API principles and microservice architecture patterns
• Familiarity with monitoring and logging tools (CloudWatch, Prometheus, Grafana, ELK Stack) and willingness to learn observability practices

Data Infrastructure & Pipeline Support

• Awareness of cloud-native data pipeline concepts and ETL/ELT principles with exposure to services like AWS S3, Lambda, Glue, or equivalent Azure/GCP services
• Basic knowledge of cloud-based data storage systems (S3, PostgreSQL, MongoDB) and understanding of differences between relational and NoSQL databases
• Foundational understanding of distributed computing and streaming concepts with exposure to frameworks like Spark, Kafka, or Ray through coursework or personal projects
• Knowledge of common data formats (JSON, CSV, Parquet, Avro) with basic understanding of schema design, data validation, and data quality considerations

Collaboration & Professional Growth

• Ability to collaborate effectively within DevOps, platform engineering, and cross-functional teams while actively seeking mentorship and learning opportunities
• Developing communication skills to document infrastructure configurations, write clear runbooks, and articulate technical challenges through team discussions and written documentation
• Enthusiastic participation in code reviews and infrastructure design discussions with openness to constructive feedback and eagerness to learn best practices
• Demonstrated ability to incorporate feedback, learn from operational incidents, and continuously improve through peer collaboration, self-study, and hands-on experience, * PhD -OR-
• MS/MA -OR-
• BS/BA and 2 years of relevant experience, * Degree in computer science, software engineering, or related technical field.
• Exposure to infrastructure automation, deployment pipelines, or cloud platform management through coursework, personal projects, labs, or internship experience.
• Basic scripting or programming experience with Python, Bash, or similar languages demonstrated through academic projects or personal automation initiatives.
• Experience with containerization (Docker) through personal projects, coursework, or labs with interest in learning Kubernetes.
• Strong problem-solving abilities demonstrated through technical challenges, troubleshooting exercises, or course projects.
• Active engagement in learning cloud technologies, automation, MLOps, or modern infrastructure practices (e.g., coursework, certifications, or technical projects)
• Participation in relevant communities, online courses (Coursera, Udemy, A Cloud Guru), or technical forums demonstrating commitment to continuous learning.

Hazardous Working Conditions/Environment

Not applicable.

Additional Information

This position requires the ability to obtain and maintain a federal security clearance.

A security clearance background investigation includes review of your employment, education, financial, and criminal history, as well as interviews with you and your personal references, neighbors, and co-workers to determine trustworthiness, reliability, and loyalty to the United States. The investigation also examines your foreign connections, drug and alcohol use, foreign influence, and overall conduct., * U.S. Citizenship

• 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).

Note: 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.

PNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual's relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.

As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.

Minimum Salary

USD $109,000.00/Yr.

Maximum Salary

USD $163,600.00/Yr.

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., Pacific Northwest National Laboratory (PNNL), is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them! At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State-the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab's campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs., 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. 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.