Senior Software Engineer III

Pacific Northwest National Laboratory•Richland, WA

4d•Onsite

About The Position

Pacific Northwest National Laboratory (PNNL) is seeking a Senior Software Engineer to join its advanced SI engineering team within the AI and Data Analytics Division of the National Security Directorate. The team develops computational solutions for complex data and analytic challenges, connecting foundational research to engineering and operations across the data analytics lifecycle. The role will build next-generation systems across agentic SI platforms, large-scale data orchestration, and real-time intelligence processing. The engineer will design scalable, mission-critical solutions, lead complex system components, mentor colleagues, and help shape technical direction. Work includes agentic SI, LLM orchestration, MLOps pipelines, multimodal data integration, microservices, real-time streaming, large-scale ETL, Kubernetes deployments, monitoring and observability, secure and edge deployments, and geospatial and time-series processing. The position also involves leading project components, making design decisions, and supporting proposals. The position is based in Richland, Washington, or Seattle, Washington, and requires onsite presence Monday through Thursday, with Friday onsite as needed based on business needs. The successful candidate must be able to obtain and maintain a federal security clearance and meet the associated eligibility requirements, including U.S. citizenship. The role is a Testing Designated Position and involves pre-employment and random drug testing. PNNL describes itself as a research institution with a diverse workforce focused on science, national security, and energy resiliency. The laboratory offers health insurance and flexible work schedules, alongside a broad benefits package. The stated salary range is USD $133,100 to $210,400 per year; actual placement depends on job-related qualifications and experience.

Requirements

Current, hands-on software development experience using Python.
One of the following education and experience combinations: PhD and 1 year of software engineering experience; MS/MA and 3 years; BS/BA and 5 years; AA and 14 years; or HS/GED and 16 years.
For the experience pathways requiring 14 or 16 years, experience must include designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development.
Strong Python skills and solid computer science fundamentals, including object-oriented design, design patterns, data structures, algorithms, and clean-code practices.
Experience or skills with Git, testing (TDD), CI/CD, and SI-assisted development tools such as Copilot, Claude, or Cursor.
Understanding of the machine learning lifecycle, model serving, and production integration via APIs.
Hands-on experience with AWS, Azure, or GCP; Docker and Kubernetes; event-driven and microservice architectures; API design (REST, GraphQL, or gRPC); and SQL/NoSQL databases.
Knowledge of ETL/ELT pipelines, distributed processing, cloud storage, and data modeling at scale.
Strong communication and engagement with cross-functional teams, Agile experience, mentorship, and pragmatic delivery.
Ability to obtain and maintain a federal security clearance and meet applicable eligibility requirements, including U.S. citizenship.
Must meet the stated drug-testing requirements, including pre-employment and random testing; the posting states that candidates must demonstrate 12 consecutive months of non-use of illegal drugs, including marijuana, before completing the requisite Questionnaire for National Security Positions.

Nice To Haves

Degree in computer science, software engineering, or a related field.
Proficiency in at least one programming language in addition to Python, such as Java, C#/.NET, C++, Go, or Rust.
Ability to contribute to technical direction and independently structure complex problems into actionable work in collaboration with senior engineers and cross-functional teams.
Experience designing or implementing components of large-scale ETL pipelines and analytics systems; petabyte-scale experience is valued.
Experience contributing to cloud-native system design, including API and microservice architecture, DevOps, containerization and orchestration (Docker/Kubernetes), infrastructure as code, and full-stack observability (logging, metrics, and tracing).
Active technical community engagement, demonstrated through meaningful open-source contributions, maintained GitHub repositories, technical blog posts or presentations, conference participation, mentoring, or self-initiated projects exploring emerging technologies.

Responsibilities

Design scalable, mission-critical software systems for advanced SI platforms, large-scale data orchestration, and real-time intelligence processing.
Build systems involving agentic SI, LLM orchestration, MLOps pipelines, and multimodal data integration.
Develop scalable infrastructure, including microservices, real-time streaming, large-scale ETL pipelines, and Kubernetes deployments.
Develop production systems involving monitoring and observability, secure and edge deployments, and geospatial and time-series processing.
Lead project components and complex system work.
Mentor junior engineers and other staff.
Drive technical design decisions and contribute to technical direction.
Translate technical requirements into working solutions and structure complex problems into actionable work.
Support proposals and collaborate with cross-functional teams.
Design or implement components of large-scale ETL pipelines and analytics systems.
Contribute to cloud-native system design, including API and microservice architecture, DevOps, containerization and orchestration, infrastructure as code, and observability.