Lead Backend Software Engineer IV; Richland, WA

Overview

At PNNL, our core capabilities are divided among major departments that we refer to as Directorates, each focused on a specific area of scientific research or 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. Additionally, 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 real‑world threats. The AI and Data Analytics Division, part of NSD, combines domain expertise with advanced hardware and software to deliver computational solutions that address complex data and analytic challenges.

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

Lead the development of mission‑critical AI systems, designing scalable microservices and distributed processing platforms for multi‑modal intelligence data at unprecedented scale and speed. Own the solution from concept to deployment, mentor staff, and collaborate with scientists and domain experts to translate cutting‑edge research into production‑ready systems deployed in highly secure environments.

• Design scalable microservices architectures and API gateways for classified environments.
• Lead distributed system design for real‑time streaming platforms handling terabytes per hour.
• Architect container orchestration and CI/CD pipelines for secure, multi‑domain deployments.
• Mentor engineering teams, drive technical decisions, and influence platform strategy across multiple development teams.

• Programming:
  Python proficiency, with experience in C#/​Net, Go, JavaScript/Type Script, Java, C/C++, or Rust.
• Cloud & Infrastructure: AWS/Azure architecture, Kubernetes, Infrastructure as Code, multi‑cloud or edge computing.
• Data & Storage: S3, Elasticsearch/Open Search, Postgre
  
  SQL, Mongo
  
  DB, Redshift, Delta Lake, vector stores.
• AI/ML Engineering:
  Agentic AI systems, LLMs, model deployment, MLOps platforms, distributed training, vector and graph analytics.
• Intelligence Systems:
  Data fusion, GEOINT processing, signals analysis, threat correlation.
• Data Engineering:
  Spark/Databricks, Kafka/streaming, data lake architectures, real‑time analytics.
• Specialized Systems:
  Geospatial processing, time‑series databases, secure enclaves.
• Leadership:
  Agile/SAFe methodologies, advanced CI/CD, security‑first Dev Ops.

• Lead technical strategy for AI‑powered national security systems, influencing platforms that process intelligence data at national scale.

• Detect and prevent smuggling of drugs and contraband at ports of entry.
• Develop large data pipelines to deter funding for terrorists, nuclear proliferators, drug cartels, and rogue leaders.
• Apply big data solutions to national security problems.
• Apply image classification for nuclear forensics analysis.
• Develop scalable geospatial analytics capabilities.

• PhD and 3 years of relevant experience – or – MS/MA or higher 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.
• Prior software development experience in designing, architecting, programming, deploying, and automating solutions for scientific research or consumer digital product development may be counted.

• Degree in computer science, software engineering, or related field.
• Expert level experience designing or deploying petabyte‑scale, high‑performance ETL pipelines and analytics.
• Fluency in Python and proficiency in at least one other language (C#/.NET, C++, Go).
• Experience leading software engineering teams and translating complex problems into actionable work.
• Experience mentoring junior staff.
• Strong understanding of software engineering and data management best practices.
• Cloud architecture expertise…