Software Engineer II

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

Core Engineering Excellence

• Working proficiency in Python with foundational knowledge of at least one additional programming language (C#/.NET, Go, C++) and eagerness to expand language skills

• Understanding of core software engineering principles including version control with Git (branching, commits, pull requests), basic automated testing (unit tests), and code quality practices (linting, formatting, code review participation)

• Familiarity with CI/CD concepts and willingness to learn DevOps practices including build automation, deployment pipelines, and continuous integration workflows

• Foundational knowledge of data structures (arrays, lists, dictionaries, trees), algorithms (searching, sorting, recursion), and willingness to learn and apply AI assist tools (e.g., GitHub Copilot, Claude, Cursor) to accelerate learning, improve code quality, and build problem-solving skills

AI/ML & Deep Learning

• Foundational knowledge of machine learning concepts including supervised/unsupervised learning, model training, and evaluation metrics with exposure to frameworks such as PyTorch, TensorFlow, or scikit-learn

• Basic understanding of the machine learning lifecycle including data preparation, model development, evaluation, and awareness of deployment and monitoring practices

• Exposure to or willingness to learn about large language model (LLM) applications, prompt engineering, and agent-based frameworks (LangChain, LlamaIndex) with ability to support AI/ML feature development

• Interest in applying ML concepts to real-world problems with eagerness to grow expertise through hands-on project work and mentorship

Cloud & Infrastructure

• Basic knowledge of cloud computing principles and familiarity with services within AWS, Azure, or GCP environments (compute, storage, networking fundamentals)

• Exposure to containerization concepts (Docker) with willingness to learn orchestration technologies (Kubernetes) and Infrastructure as Code practices (Terraform, CloudFormation)

• Understanding of RESTful API principles including HTTP methods, status codes, JSON data exchange, and basic microservice architecture concepts

• Foundational knowledge of database systems including relational databases (PostgreSQL, MySQL) and/or NoSQL options (MongoDB, DynamoDB) with understanding of when to use each

Data Engineering & Storage

• Awareness of cloud-native data pipeline concepts and ETL/ELT principles with exposure to services such as AWS S3, Lambda, Glue or equivalent Azure/GCP services

• Basic knowledge of cloud-based data storage systems (S3, PostgreSQL, MongoDB) and understanding of different storage paradigms (object storage, relational, document-based)

• Foundational understanding of distributed computing concepts and exposure to frameworks like Spark, Kafka, or Ray with willingness to learn streaming architectures and parallel processing

• Knowledge of common data formats (JSON, CSV, Parquet) with basic understanding of schema design principles, data validation, and data quality considerations

Collaboration & Professional Growth

• Ability to collaborate effectively within cross-functional teams including senior engineers, data scientists, and product stakeholders while actively seeking mentorship and learning opportunities

• Developing communication skills to articulate technical challenges and solutions through clear documentation, team discussions, and willingness to ask clarifying questions

• Enthusiastic participation in code reviews with openness to constructive feedback, eagerness to learn best practices, and growing ability to provide helpful code review comments

• Demonstrated ability to incorporate feedback, learn from mistakes, and continuously improve technical skills through peer collaboration, self-study, and hands-on experience

National Interest Project Examples, + 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) ], + PhD -OR-

• MS/MA -OR-

• BS/BA and 2 years of relevant experience

Preferred Qualifications:

• Degree in computer science, software engineering, or related field

• 2+ years of professional software development experience or relevant internship experience building production-quality software

• Demonstrated technical contributions through personal projects, open-source contributions, academic projects, or internships showing practical application of software engineering skills

• Exposure to data processing, ETL pipelines, or analytics systems through coursework, personal projects, or professional experience

• Experience with any cloud platform (AWS, Azure, GCP) through certifications, coursework, or hands-on projects

• Programming experience beyond academic settings including hackathons, coding competitions, or personal software projects

• Strong problem-solving abilities demonstrated through technical challenges, algorithms practice, or project troubleshooting

• Demonstrated self-directed learning and technical initiative through personal projects, GitHub repositories, open-source contributions, technical blog posts, online course completion, hackathon participation, or active engagement in technical communities showcasing curiosity and motivation beyond academic requirements

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.

Requirements:

• 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.