Senior Software Engineer, Agentic AI

Senior Software Engineer

At PNNL, our core capabilities are divided among major departments referred 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, consists of over 400 staff and 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.

We are seeking an experienced Senior Software Engineer to drive the design, development, execution, and integration of groundbreaking agentic AI agents. This role is perfect for engineers passionate about building tools for other developers, working across diverse technology stacks, and shaping the future of AI enablement in production environments.

This role is unique. It isn't just about building AI agents and working with agentic frameworks. We're looking for someone with a deep understanding of what it takes to build highly scalable systems from scratch, pulling on experience in IaC, DevOps, MLOps, Data Engineering and more. We're looking for someone who consistently seeks out and employs new technology on increasingly complex problems, and who can transform those complex problems into tractable solutions. A coder, designer, architect, leader and engineer with a penchant for working closely with data scientists and wrangling and submitting data to large-scale AI and ML implementations.

You will partner with cross-functional teams to advance developer tooling, enhance agent authentication and orchestration frameworks, and create impactful real-world demos.

Responsibilities Include:

• Design and deploy scalable AI systems capable of dynamic reasoning and actionable decision-making
• Build and optimize infrastructure, leveraging containerization tools and automated CI/CD pipelines for efficient AI deployment
• Develop and manage robust data pipelines for sourcing, preprocessing, and experimentation
• Monitor system performance, troubleshoot issues, and ensure compliance with ethical AI standards
• Collaborate across engineering, product, and security teams to align systems with organizational goals and industry regulations
• Create developer-focused tooling and maintain high-quality documentation, including API references, quick starts, and best practices for AI-native frameworks
• Lead the integration of emerging AI frameworks by developing adapters, utilities, interfaces, and orchestration layers
• Contribute to engineering standards by driving design discussions and shaping team-wide architectural decisions
• Ensure resilience and security in agent-to-agent and model-to-service communications
• Mentor and guide junior scientists and engineers while fostering a collaborative team environment

This position is onsite and requires onsite work in either Richland, WA or Seattle, WA.

Minimum Qualifications:

• 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
• Qualifying software development experience in designing, architecting, programming, deploying, and automating software solutions in support of scientific research or consumer digital product development may be counted

Preferred Qualifications:

• Demonstrated expertise in designing and deploying agentic AI systems in real-world applications.
• Experience engaging with funding agencies such as the Department of Energy, National Nuclear Security Administration, Department of Defense, or Department of Homeland Security, and demonstrated ability to initiate substantial new R&D efforts and collaborations.
• Demonstrated experience in applying AI to scientific challenges, such as solving problems in energy systems, climate modeling, materials design, or molecular science.
• Expert-level software engineering: Git-based workflows, code reviews, automated testing, CI/CD pipelines, static analysis, thorough documentation, secure coding practices, performance profiling, and Agile/DevOps methodologies.
• Cloud-native system design: API and microservice architecture, containerization and orchestration (Docker/Kubernetes), infrastructure as code, and full-stack observability (logging, metrics, tracing).
• Mature MLOps capabilities: experiment tracking, model and data versioning, automated deployment/rollback, monitoring, and governance of production ML services.
• Fluency in Python and proficiency in at least one additional language (e.g., C++ or Go).
• Hands-on experience with leading deep-learning frameworks (PyTorch, TensorFlow, or JAX).
• Deep, practical expertise with modern LLM-orchestration and agent frameworks (LangChain, LlamaIndex, etc.) and related open-source tooling.
• Solid understanding of system design, microservice architecture, and distributed computing; experience scaling ML workloads with Kubernetes, Ray, Spark, or similar technologies.
• Production experience on major cloud platforms (AWS, Azure, GCP) and/or secure edge deployments.
• Experience integrating multi-modal data sources (text, vision, structured/sensor data) into cohesive reasoning or decision pipelines.
• Familiarity with state-of-the-art generative AI techniques: LLM fine-tuning (LoRA/PEFT, QLoRA over SLM, data set preparation), retrieval-augmented generation, prompt engineering, and evaluation.
• Contributions to open-source AI ecosystems (e.g., Hugging Face, LangChain, Llama) or peer-reviewed publications.
• Collaborative, self-directed problem solver who can translate ambiguous requirements into actionable technical roadmaps and mentor junior staff.
• Demonstrated written and verbal communication skills; ability to convey complex ideas to technical and non-technical audiences.

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.

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