Senior Software Engineer, Agentic AI

Pacific Northwest National Laboratory•Richland, WA

3h•Onsite

About The Position

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

Requirements

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

Nice To Haves

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.

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

Benefits

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.

Stand Out From the Crowd

Upload your resume and get instant feedback on how well it matches this job.

Upload and Match Resume