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Argonne National Laboratory

Advanced scientific research and computing facilities

DevOps Engineer

Full-Time
$69.8k - $108.8k
Junior
Bachelor's
Lemont, IL, USA
HybridHybrid schedule includes some on-site and remote days; employees typically work more than 60% remotely.
DevOps & InfrastructureDevOps Engineering
No H1B Sponsorship
US Citizenship Required

About the job

Requirements
  • A Bachelor's degree in computer science or a closely related field and at least 2 years of experience as a DevOps engineer and/or Cloud Engineer.
  • Previous experience as a team lead, with the ability to perform task management for DevOps or Cloud Engineering teams.
  • Working knowledge of cloud application architecture patterns and common products and managed services for at least one Cloud Service Provider, such as AWS.
  • Working knowledge of Kubernetes cluster administration and concepts, including CR/CRDs, and application deployment strategies such as GitOps and Helm.
  • Working knowledge of Unix system fundamentals and common network protocols.
  • A solid understanding of cloud computing networking concepts.
  • The ability to proactively identify performance issues, problems, and areas for improvement.
  • The ability to identify requirements and define, plan, and implement requisite solutions.
  • The ability to plan, organize, prioritize tasks, and complete assigned projects with minimal supervision.
  • Experience with continuous integration and continuous deployment software methodologies and strategies.
  • An understanding of code review and familiarity with tools such as GitHub and GitLab.
  • Experience using tools such as Nagios, Grafana, and Prometheus to monitor systems and metrics and create dashboards.
  • Experience with OpenTofu or Terraform in multi-account AWS environments, including AWS Organizations, SCPs, and IRSA (IAM Roles for Service Accounts).
  • Hands-on experience with ArgoCD, including App of Apps patterns and ApplicationSets for multi-environment GitOps deployments.
  • Familiarity with Tanka, Jsonnet, or equivalent configuration-as-code templating approaches beyond Helm.
  • Experience with Kong Gateway or similar API gateway platforms in Kubernetes environments.
  • Familiarity with secrets management patterns, including AWS Secrets Manager, External Secrets Operator, or comparable Kubernetes-native solutions.
  • The ability to model Argonne's Core Values: Impact, Safety, Respect, Integrity, and Teamwork.
  • Successful applicants must provide proof of U.S. citizenship to perform the essential functions of the position and comply with federal regulations and contract requirements.
Responsibilities
  • Perform cluster administration and assist users with application deployment for the Kubernetes-based service stack.
  • Build and maintain pipelines for deploying cloud infrastructure and science services.
  • Manage and use image registries such as Harbor.
  • Write and update automation for resource provisioning and CI/CD pipelines using tools such as Terraform, GitOps, and Python.
  • Implement security controls defined by the Cybersecurity team as part of DevSecOps.
  • Configure basic instrumentation for infrastructure and core services to feed monitoring and alerting systems.
  • Provide primary operational support and engineering for production applications.
  • Define and implement key performance indicators and processes, and drive continuous improvement.
  • Diagnose platform operational problems quickly and effectively.
  • Deploy, manage, and operate managed Kubernetes clusters such as Amazon EKS, Azure AKS, and Google GKE, including node group lifecycle management, cluster upgrades, cloud-native networking integrations such as load balancer controllers and CNI plugins, and multi-environment promotion across development, staging, and production.
  • Coordinate with vendors to resolve hardware and software problems.
Desired Qualifications
  • Exposure to high-speed research networks such as ESnet or Internet2.

About the company

A

Argonne National Laboratory

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Argonne National Laboratory advances scientific discovery and sustainability by providing access to large-scale research facilities and high-performance computing for government, academia, and industry partners. Researchers use the Advanced Photon Source for atomic-level materials studies and the Argonne Leadership Computing Facility for complex simulations and data analysis. The lab differentiates itself through its shared-use, multi-institution partnerships and a focus on eco-innovation, net-zero goals, and AI accelerator development. Its aim is to address real-world energy, materials, and data science challenges by combining cutting-edge infrastructure with collaborative research efforts.

Company Size

5,001-10,000

Company Stage

Grant

Total Funding

$19.7M

Headquarters

Lemont, Illinois

Founded

1946

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Simplify Jobs

Simplify's Take

What believers are saying

  • UChicago Argonne LLC won a renewed DOE contract in 2026 for five years.
  • 2026 launch of ChemGraph, GridMind, and AI inference services deepens Argonne's relevance.
  • Activated Materials Lab opened in 2026, expanding nuclear fuels research and user-facility demand.

What critics are saying

  • DOE's FY2027 request cuts Argonne funding about $155.8 million, hitting programs and construction.
  • 2025 buyouts showed staff pressure; more layoffs follow if Congress accepts budget cuts.
  • A prolonged federal reset or shutdown threatens APS, Aurora utilization, and Argonne's operating model.

What makes Argonne National Laboratory unique

  • Aurora and APS create a rare AI-plus-X-ray discovery stack for 2026 science.
  • Chain Reaction Innovations embeds startups inside Argonne with facilities, mentors, and DOE funding.
  • Q-NEXT and other DOE centers keep Argonne central to U.S. quantum research.

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Benefits

  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Life Insurance
  • Disability Insurance
  • Paid Vacation
  • Paid Sick Leave
  • Paid Holidays
  • Remote Work Options
  • Flexible Work Hours
  • 401(k) Retirement Plan
  • 401(k) Company Match

Growth & Insights and Company News

6 month growth

1%

1 year growth

1%

2 year growth

1%
The Register
Oct 7th, 2026
Argonne's AI X-ray nanoprobe beamline responds to natural language commands to analyse samples

Scientists at Argonne National Laboratory have developed an AI-enhanced X-ray microscope that researchers can control using natural language commands. The system combines an agentic AI platform with a hard X-ray nanoprobe beamline, allowing users to simply ask the microscope to examine specific areas of interest. The technology addresses a major challenge in X-ray imaging: modern experiments can generate millions of images in hours, requiring days of conventional analysis. Argonne's AI system reconstructs images in real time as data arrives. The microscope can autonomously collect data, process results, and identify additional areas requiring investigation. Computational scientist Mathew Cherukara said the AI-enhanced microscope could benefit numerous scientific fields beyond its initial microelectronics demonstration. The project forms part of the SYNAPS-I initiative, led by Lawrence Berkeley National Laboratory under the Department of Energy's Genesis Mission, launched in November 2025.

Associated Press
Jul 7th, 2026
Argonne's ChemGraph uses AI to automate computational chemistry workflows

Researchers at the US Department of Energy's Argonne National Laboratory have developed ChemGraph, an open-source framework that uses artificial intelligence to automate computational chemistry workflows. The tool provides a natural language interface, allowing researchers to describe scientific problems in plain language, which the system then maps onto computational tasks and analyses. ChemGraph was developed using resources at the Argonne Leadership Computing Facility, including the Aurora exascale supercomputer. The framework uses AI agents to handle different workflow tasks, from planning to execution and data aggregation. It calls appropriate scientific tools to reduce the risk of AI hallucination, using AI to run physics-based simulations rather than relying solely on existing knowledge. The framework supports applications in combustion efficiency, critical materials, and next-generation batteries, and complements DOE's Genesis Mission to accelerate science through AI.

The Register
May 27th, 2026
Argonne National Laboratory launches private AI inference service using spare supercomputer capacity

The US Department of Energy's Argonne National Laboratory has launched an AI inference service using spare supercomputing capacity to support researchers across DoE labs and the Genesis Mission. The service runs on two clusters: Sophia, with 192 Nvidia A100 GPUs, and Metis, featuring 32 SambaNova SN40L AI accelerators. The platform provides secure access to various large language models, including OpenAI's GPT-OSS, Google's Gemma, and Meta's Llama, through a chatbot-like portal. Researchers are using the service to analyse experimental data in real time, including predicting plasma disruptions in fusion energy research and processing data from particle accelerators and telescopes. Argonne plans to extend the service to its Nvidia GH200-based Tara and B200-based Minerva systems, enabling scientists to experiment with AI without building their own infrastructure.

Business Wire
Mar 26th, 2026
Argonne Lab develops GridMind AI agent to support power grid operators

Researchers at the US Department of Energy's Argonne National Laboratory have developed GridMind, an agentic AI system designed to assist power grid operators through natural language interaction. The system functions as a reasoning co-pilot for control rooms, simplifying complex grid management tasks. GridMind employs a multi-agent architecture where specialised AI agents handle different functions, such as power scheduling and weather-based contingency planning. Large language models coordinate these agents to analyse situations, reason across different tasks and provide explainable recommendations. The system transforms technical analysis into conversational support whilst maintaining rigorous accuracy. Tests on standard power grid models demonstrated that GridMind consistently produced correct results across multiple state-of-the-art language models. The technology aims to accelerate decision-making by integrating disconnected workflows into a coherent reasoning engine.

Yahoo Finance
Mar 11th, 2026
AI adviser helps Argonne's robotic lab discover advanced electronic materials in just 64 experiments

A research team led by the US Department of Energy's Argonne National Laboratory has developed an AI adviser that optimises machine learning algorithms during autonomous experiments, accelerating discovery of advanced electronic materials. The system was applied to Polybot, Argonne's AI-guided robotic laboratory, to investigate mixed ion-electron conducting polymers for wearable electronics and energy storage. The adviser evaluates algorithm performance in real time and communicates insights to scientists who refine experimental plans. It reduced the study to just 64 experiments from over 4,300 possible combinations. During testing, the adviser suggested switching AI algorithms, leading to significant performance improvements, and identified deposition speed as a key performance driver. The research was published in Nature Chemical Engineering and included collaborators from the University of Chicago, Lawrence Berkeley National Laboratory and other institutions.