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Software Engineer II

LinkedIn Pacific Northwest National Laboratory Seattle, WA
Not Applicable Posted March 27, 2026 Job link
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Requirements
  • 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]
  • Develop large data pipelines to thwart funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders [Link]
  • Applying big data solutions to national security problems [Link]
  • Applying image classification for nuclear forensics analysis [Link]
  • Develop capabilities for scalable geospatial analytics [Link]
  • MS/MA -OR
  • BS/BA and 2 years of relevant experience
  • 2+ years of professional software development experience or relevant internship experience building production-quality software
  • Exposure to data processing, ETL pipelines, or analytics systems through coursework, personal projects, or professional experience
  • This position requires the ability to obtain and maintain a federal security clearance.
  • 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).
  • Department of Energy if non-use of illegal drugs, including marijuana, for 12 months cannot be demonstrated.
Preferred Skills
  • 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
  • Foundational knowledge of database systems including relational databases (PostgreSQL, MySQL) and/or NoSQL options (MongoDB, DynamoDB) with understanding of when to use each
  • Basic knowledge of cloud-based data storage systems (S3, PostgreSQL, MongoDB) and understanding of different storage paradigms (object storage, relational, document-based)
  • 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
Education
  • (Not required) – PhD -OR
  • (Not required) – MS/MA -OR
  • (Not required) – BS/BA and 2 years of relevant experience
  • (Not required) – Degree in computer science, software engineering, or related field