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Argonne National Laboratory

Argonne National Laboratory

Advanced scientific research and computing facilities

Associate Division Director - APS Engineering Support, Aes

Full-Time
$202.1k - $315.3k/yr
Expert
Master's, PhD
Woodridge, IL, USA
In Person

On-site in Lemont, IL; occasional domestic and international travel.

Company Does Not Provide H1B Sponsorship

About the job

Requirements
  • Master’s degree in engineering, computer science, mechanical systems engineering, engineering physics, or a related technical discipline; equivalent combination of education and experience will be considered.
  • A minimum of fifteen (15) years of progressively increasing responsibility in engineering or a closely related technical discipline, including at least ten (10) years of experience leading multidisciplinary technical teams or organizations, with a proven history of delivering strategic initiatives, complex engineering programs, and organizational results.
  • Demonstrated experience managing managers, i.e., leading an organization through group leaders responsible for their own staff and technical scope.
  • Demonstrated experience developing and executing organizational strategy, managing budgets, and leading through organizational change.
  • Strong written and verbal communication skills, including the ability to represent the organization effectively to senior laboratory leadership, external stakeholders, technical staff, and users.
  • Demonstrated commitment to safety, quality, and a positive, inclusive work culture.
  • Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork.
  • Interpersonal skills, oral and written communication skills, and ability to interact with people at all levels both within and outside the laboratory.
Responsibilities
  • Provide senior leadership, direction, mentorship, and performance management to the leaders of the Information Solutions, Information Technology, and Mechanical Design and Drafting groups, and, through them, to the staff of those groups.
  • Serve as a member of the AES senior leadership team, contributing to division-wide strategy, workforce planning, budget development, and operational decision-making.
  • Foster a culture of safety, technical excellence, professional development, inclusion, and cross-group collaboration; act as a role model for the Argonne Core Values.
  • Recruit, retain, and develop a functionally diverse and high-performing workforce; oversee succession planning for key technical and leadership positions within the portfolio.
  • Set the strategic direction for the assigned groups in alignment with AES and APS priorities and translate that direction into an actionable roadmap with clear phases, milestones, deliverables, and measurable outcomes.
  • Develop the tactical implementation plans required to deliver on the roadmap: define scope, sequencing, resource commitments, dependencies, decision gates, and risk mitigations; validate that plans are executable within the available capacity and budget; and secure commitment from the responsible group leaders and stakeholders.
  • Drive the successful execution of those plans through active operational leadership: hold groups accountable to committed milestones and outcomes; anticipate and address risks and blockers early; adjust the plan when circumstances change without losing sight of strategic intent; and personally intervene when a critical initiative is at risk.
  • Lead the AES contribution to enterprise digital initiatives — modernization of the digital infrastructure, integration and rationalization of engineering business systems, and establishment of a unified engineering data thread across the organization — from mission need definition through detailed implementation to sustained operation.
  • Champion and personally own the modernization of mechanical design and drafting capabilities, including CAD, PLM, and digital engineering workflows; ensure that the transition from current state to modernized capability is delivered on schedule and produces measurable improvements in productivity, quality, and traceability.
  • Establish and monitor implementation metrics — milestone completion, budget adherence, service-level performance, and customer outcomes — and report progress transparently to the AES Division Director, division leadership, and stakeholders; use the resulting data to drive continuous improvement in how the portfolio delivers.
  • Partner with peer leaders across AES, the Accelerator Division, the X-ray Science Division, and Argonne central services to align priorities, resolve cross-division dependencies during implementation, and secure the stakeholder engagement necessary for change to be adopted and sustained.
  • Build and sustain the internal capacity — talent, processes, tools, and culture — required for the portfolio to execute complex, multi-year initiatives reliably, and institutionalize successful practices so that improvements outlast individual projects.
  • Ensure the safe, compliant, and reliable operation of the groups within the portfolio, including compliance with Argonne, DOE, and other applicable requirements.
  • Oversee the operational planning and delivery of information technology, information solutions, and mechanical design and drafting services in support of APS operations, projects, and scientific user programs.
  • Manage annual operating budgets and long-term capital planning for the portfolio; establish and monitor performance measures for service delivery, reliability, and cost effectiveness.
  • Ensure that engineering design and drafting output meets applicable standards for quality, configuration control, and long-term maintainability.
  • Represent AES to Argonne senior leadership, DOE program offices, external review committees, and the user community as appropriate.
  • Participate in laboratory-wide committees, working groups, and initiatives, particularly those affecting information technology, digital engineering, or engineering design across Argonne.
  • Support the AES Division Director on strategic initiatives, including organization efforts intended to consolidate and modernize the engineering enterprise supporting the APS.
Desired Qualifications
  • Doctoral degree in engineering, physics, computer science, or related discipline.
  • Experience in a national laboratory, major research facility, or scientific user facility environment, including familiarity with 24/7 operations, safety programs, and Department of Energy requirements.
  • Experience with digital transformation programs, including product lifecycle management (PLM), MBSE, AI for operations and engineering, computerized maintenance management systems (CMMS), digital thread implementations, or equivalent enterprise engineering data platforms.
  • Experience with engineering design and drafting tools and processes, including CAD systems and configuration management practices for engineered assets.
  • Familiarity with EPICS-based control systems and scientific computing environments.
  • Experience leading organizational transitions, including matrixed working arrangements across scientific and engineering divisions.
  • Familiarity with DOE Order 413.3B or equivalent project management frameworks.

About the company

Argonne National Laboratory

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'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

Professional Development Budget

Wellness Program

Growth & Insights and Company News

Headcount

6 month growth

-2%

1 year growth

-2%

2 year growth

-2%
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.

Argonne National Laboratory
Jun 2nd, 2022
5 clean energy startups chosen for Argonne’s Chain Reaction Innovations - Chain Reaction Innovations

An energy and science incubator for transformative technologies