Lead Software Engineer IV

Overview
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.
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 uniquely combines deep technical leadership in scalable system design with hands-on expertise in modern AI/ML engineering, requiring someone who can operate with both strategic vision and tactical excellence.
Who You Are
You're an experienced engineer who seamlessly bridges infrastructure, AI/ML systems, and production-grade software development. You've built highly scalable systems from scratch, led technical initiatives that matter, and have a track record of transforming complex problems into tractable solutions. You're equally comfortable architecting distributed systems processing terabytes per hour as you are fine-tuning LLMs or building developer tooling. You bring startup agility to mission-critical work where failure isn't an option.
What You'll Build
AI-Native Systems & Platforms

Design and deploy scalable agentic AI systems with dynamic reasoning and decision-making capabilities
Architect LLM orchestration frameworks using LangChain, LlamaIndex, and emerging agent platforms
Build MLOps platforms spanning experiment tracking, model versioning, deployment, and governance
Develop developer-focused tooling, adapters, and interfaces for AI-native frameworks
Integrate multi-modal data sources (text, vision, structured/sensor data) into cohesive reasoning pipelines
Scalable Infrastructure & Data Systems

Design microservices architectures coordinating across multiple domains and security enclaves
Lead distributed system design processing data from hundreds of sources simultaneously
Architect real-time streaming platforms handling terabytes per hour with event-driven architectures
Build robust data pipelines for petabyte-scale ETL, data lake/mesh architectures, and real-time analytics
Design container orchestration (Kubernetes) and CI/CD pipelines for classified and edge environments
Mission-Critical Production Systems

Deploy AI systems in highly secure environments with resilient agent-to-agent communications
Create monitoring and observability systems (logging, metrics, tracing) across secure enclaves
Ensure compliance with ethical AI standards and security-first DevOps practices
Build geospatial processing, time-series, and intelligence data fusion capabilities
Technical Leadership

Lead a team of engineers to deliver on high risk / high impact ambiguous technical scope
Drive technical strategy and architectural decisions across cross-functional teams
Translate ambiguous requirements and cutting-edge research into actionable technical roadmaps
Lead design discussions shaping team-wide engineering standards
Mentor engineering teams and guide junior scientists/engineers
Technical Knowledge, Skills, And Abilities
Technical Leadership & Engineering Excellence

Demonstrated fluency in Python and proficiency in at least one additional language (C#/.NET, Go, C++) with ability to architect solutions and guide language selection decisions across complex, multi-language codebases
Proven track record of establishing and championing software engineering best practices including version control strategies, comprehensive automated testing frameworks, code quality standards, and technical documentation across engineering teams
Expert-level proficiency in designing and implementing sophisticated CI/CD pipelines with ability to define DevOps strategies, build/release processes, and deployment architectures that ensure reliable, secure, and efficient software delivery at scale
Seasoned practitioner with ability to lead engineering teams in defining technical specifications, architectural patterns, and system designs for microservices, distributed systems, and large-scale applications while strategically leveraging AI assist tools to accelerate team productivity and drive innovation
AI/ML Systems Architecture & Implementation

Proven experience architecting, implementing, and deploying production-grade agentic AI systems with multi-step reasoning, autonomous workflows, and decision-making capabilities into operational environments at scale
Deep practical expertise with deep learning frameworks (PyTorch, TensorFlow, JAX) and LLM orchestration platforms (LangChain, LlamaIndex, LangGraph) with ability to design complex AI applications, custom chains, retrieval systems, and agent-based architectures
Advanced expertise in LLM optimization techniques including fine-tuning methodologies (LoRA/PEFT, QLoRA), retrieval-augmented generation (RAG) system design, prompt engineering strategies, and comprehensive evaluation frameworks
Comprehensive understanding of the end-to-end machine learning lifecycle with proven ability to architect and build production ML platforms including feature engineering pipelines, model serving infrastructure, monitoring, and automated retraining systems
Cloud Architecture & Distributed Systems

Demonstrated expertise architecting and deploying enterprise-scale applications across cloud platforms (AWS, Azure, GCP) with ability to design multi-cloud strategies and advanced proficiency in containerization (Docker) and orchestration technologies (Kubernetes) including Infrastructure as Code practices
Expert ability to architect and implement sophisticated event-driven systems using message brokers (Kafka, RabbitMQ), pub/sub patterns, and serverless functions with consideration for exactly-once semantics, ordering guarantees, and failure handling
Mastery of cloud native API design patterns including RESTful principles, GraphQL schemas, and gRPC services with proven experience establishing API standards, versioning strategies, and microservice communication patterns for large-scale distributed systems
Deep understanding of data storage architecture including relational databases (PostgreSQL, MySQL), NoSQL systems (MongoDB, DynamoDB, Cassandra), and data warehouses (Redshift, Snowflake, BigQuery) with ability to design polyglot persistence strategies optimized for specific workload characteristics
Data Platform Engineering & Distributed Processing

Mastery of cloud-native data pipeline architectures including ETL/ELT design patterns, orchestration frameworks (Airflow, Prefect, Step Functions), and cloud services (AWS Glue, Lambda, Azure Data Factory) with ability to architect enterprise-scale data platforms
Expert knowledge of distributed data storage systems (S3, Redshift, Delta Lake, PostgreSQL, MongoDB, OpenSearch, Databricks) with proven ability to design data lakehouse architectures and advanced proficiency with distributed computing frameworks (Spark/Databricks, Kafka, Flink, Ray)
Demonstrated expertise deploying and optimizing scalable ML workloads on distributed platforms using Kubernetes, Ray clusters, or Spark with deep understanding of data modeling principles including schema design, normalization/denormalization strategies, and data quality frameworks
Proven ability to architect petabyte-scale data systems with appropriate partitioning strategies, indexing approaches, and query optimization patterns while mastering data format selection (Parquet, Avro, ORC, Delta, Iceberg) for optimal compression, performance, and schema evolution
Data Platform Engineering & Distributed Processing

Proven ability to lead and mentor engineering teams through technical challenges, architecture discussions, and knowledge sharing while establishing team standards for code quality, testing practices, and architectural patterns through mentorship and leading by example
Expert communication skills to articulate complex technical concepts, system designs, and strategic recommendations to diverse audiences including engineering teams, executive leadership, and stakeholders through comprehensive documentation, architecture decision records, and presentations
Strategic ability to balance competing priorities including technical excellence, delivery velocity, technical debt management, and innovation while making pragmatic trade-offs that align with organizational objectives
Experience leading technical planning initiatives including system architecture design, technology evaluation, and roadmap development with proven capability to drive cross-functional collaboration and champion process improvements while demonstrating adaptability to rapidly evolving technical landscapes
What Makes This Role Unique
You'll operate at the intersection of cutting-edge AI research and production systems engineering, building platforms that process the nation's most sensitive intelligence data while mentoring teams and shaping technical strategy. You'll work with startup agility on problems of national importance, rapidly iterating solutions that push the boundaries of what's possible in AI and distributed systems.
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]
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.
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.
Preferred Qualifications

Degree in computer science, software engineering, or related field
7+ years of professional software engineering experience with at least 3-5 years in technical leadership or senior engineering roles
Track record of leading development of production systems serving significant user bases or processing substantial data volumes
Experience building and leading high-performing engineering teams through mentorship and professional development
Demonstrated experience leading teams of software engineers and translating complex technical problems into structured, actionable work
Experience establishing engineering practices, architectural standards, and technical strategies at organizational scale
Background in multiple domains (AI/ML, distributed systems, data engineering, cloud infrastructure) with ability to bridge technical disciplines
Prior experience in mission-critical, regulated, or high-security environments (government, defense, healthcare, financial services)
Established thought leadership and technical influence through substantial open-source maintainership, published technical articles or conference talks, recognized expertise in specific domains, community building initiatives, or side projects that have driven innovation—demonstrating sustained commitment to advancing the profession and elevating others in the technical community
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.
“Referral Eligible”
Testing Designated Position
This position is a Testing Designated Position (TDP). The candidate selected for this position will be subject to pre-employment and random drug testing for illegal drugs, including marijuana, consistent with the Controlled Substances Act and the PNNL Workplace Substance Abuse Program.
About PNNL
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.
Commitment to Excellence and Equal Employment Opportunity
Our laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.
Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.
We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov.
Drug Free Workplace
PNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.
If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.
Security, Credentialing, And Eligibility Requirements
As a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For Foreign National Candidates
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Mandatory Requirements
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.
Rockstar Rewards
Employees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance*, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company-funded pension plan* and may enroll in our 401 (k) savings plan with company match*. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.

Research Associates excluded.
All benefits are dependent upon eligibility.
Click Here For Rockstar Rewards
Notice to Applicants
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 $161,300.00/Yr.
Maximum Salary
USD $255,000.00/Yr.