Lead Software Engineer IV

At PNNL, our core capabilities are divided among major departments called Directorates, each focused on a specific area of scientific research or function. The National Security Directorate (NSD) drives science-based, mission-focused solutions to address complex, real-world threats. The AI and Data Analytics Division, part of NSD, combines domain expertise with advanced hardware and software to deliver computational solutions for complex data and analytic challenges. Working in multidisciplinary teams, we connect foundational research to engineering and operations, providing tools to innovate quickly and field results faster.

Responsibilities

We are seeking an exceptional Lead Software Engineer to architect and build next-generation AI systems at PNNL, spanning agentic AI platforms, petabyte-scale data orchestration, and real-time intelligence processing that define the future of national security technology. This role blends deep technical leadership with hands-on AI/ML engineering, requiring both strategic vision and tactical excellence.

• AI-Native Systems: Agentic AI with dynamic reasoning, LLM orchestration (LangChain, LlamaIndex, LangGraph), MLOps platforms, and multi-modal reasoning pipelines
• Scalable Infrastructure: Microservices across security enclaves, real-time streaming (TB/hour), petabyte-scale ETL, data lake/mesh architectures, and Kubernetes/CI-CD for classified & edge environments
• Production Systems: Secure AI deployments, observability across enclaves, ethical AI compliance, and geospatial/time-series intelligence data fusion
• Technical Leadership: Lead engineers on high-impact ambiguous scope, drive architecture and strategy, build roadmaps from cutting-edge research, and mentor teams

Requirements

• Engineering Leadership: Expert Python + another language (C#/.NET, Go, C++); proven track record establishing best practices, advanced CI/CD, and architecting distributed systems
• AI/ML Architecture: Production agentic AI experience; deep expertise with PyTorch/TensorFlow/JAX and LLM orchestration; advanced LLM optimization (LoRA/PEFT, RAG, fine-tuning); end-to-end ML platform design
• Cloud & Distributed Systems: Enterprise-scale architecture across AWS/Azure/GCP; Docker/Kubernetes/IaC; event-driven systems (Kafka, RabbitMQ); API design mastery (REST, GraphQL, gRPC); polyglot persistence (SQL/NoSQL/warehouses)
• Data Platform Engineering: Cloud-native pipelines & orchestration (Airflow, Prefect); data lakehouse architectures; distributed computing (Spark, Flink, Ray); petabyte-scale optimization and modern data formats (Parquet, Iceberg, Delta)
• Leadership & Communication: Mentoring teams, articulating strategy to executives & stakeholders, balancing delivery with technical excellence, and driving cross-functional collaboration

Qualifications

Minimum Qualifications:

• PhD and 3 years of Software Engineering experience OR
• MS/MA and 5 years of Software Engineering experience OR
• BS/BA and 7 years of Software Engineering experience OR
• AA and 16 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development OR
• HS/GED and 18 years of Software Engineering experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development
• Current, hands-on software development experience using Python

Preferred Qualifications:

• Actively using Python and have been doing so for the previous five years
• Expert-level Python: Architecting production frameworks, libraries, and large multi-language codebases at scale
• Enterprise ETL/data platform leadership: Designing petabyte-scale ETL/ELT pipelines, orchestration (Airflow, Prefect, Step Functions), and data lakehouse architectures
• Advanced cloud architecture: Multi-cloud strategy across AWS, Azure, or GCP with Kubernetes and Infrastructure as Code at enterprise scale
• FFRDC or national laboratory experience: Prior work within a Federally Funded Research and Development Center or DOE national lab environment
• National security / intelligence experience: Supporting government, defense, or intelligence programs, including classified and compliance-driven environments
• Production agentic AI / advanced LLM experience: Deploying autonomous agent systems, RAG, and fine-tuned models in operational environments
• Distributed ML at scale: Deploying and optimizing ML workloads on Ray, Spark, or Kubernetes clusters
• Technical team leadership: Proven experience leading engineering teams through ambiguous, high-impact scope

National Interest Project Examples

• Detect and prevent smuggling of drugs and contraband at ports of entry
• Develop large data pipelines to thwart 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 capabilities for scalable geospatial analytics

Schedule

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

Additional Information

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

• 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, requiring pre-employment and random drug testing. Applicants must demonstrate non-use of illegal drugs, including marijuana, for the 12 consecutive months preceding completion of the requisite Questionnaire for National Security Positions (QNSP).