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Pacific Northwest National Laboratory · 2 weeks ago

Senior Software Engineer, Agentic AI

Richland, WA

Full-time

Onsite

Mid, Senior Level

$161K/yr - $255K/yr

3+ years exp

Pacific Northwest National Laboratory (PNNL) is a world-class research institution focused on scientific research and innovation. They are seeking an experienced Senior Software Engineer to design, develop, and integrate agentic AI systems, collaborating with cross-functional teams to enhance developer tooling and create impactful AI solutions.

Biomass EnergyEnergyGovernmentProduct ResearchSecurity

Growth Opportunities

No H1B

Security Clearance Required

U.S. Citizen Only

Responsibilities

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

Qualification

Agentic AI systemsCloud-native designMLOps capabilitiesDeep-learning frameworksPythonContainerization toolsCI/CD pipelinesMicroservice architectureCollaborationProblem solvingCommunication skills

Required

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

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)

Preferred

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