Research Associate, Agentic Workflows

Oak Ridge National Laboratory; Oak Ridge (TN); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Flexible hybrid/onsite schedule

On-site fitness facilities

Job summary

Oak Ridge National Laboratory (ORNL) seeks a senior contributor to design provenance and workflow systems for autonomous, AI-driven science. You will instrument distributed workflows, support cross-facility data and model artifact tracking, and translate scientific needs into scalable, auditable automation.

You will collaborate with researchers across DOE facilities, contribute to open-source software, and publish results in premier venues.

Qualifications

• PhD in CS/CE or MS with related experience.
• Experience designing or operating distributed systems or orchestration frameworks.
• Familiar with agentic workflows or AI agent frameworks.
• At least 1 year of Python; Bash and/or C/C++ experience.
• Experience with Linux HPC environments and job schedulers.

Responsibilities

• Develop provenance capture and data integration for scalable workflows.
• Support cross-facility integration, schemas, APIs and metadata standards.
• Assist platform integration and architectural trade-offs toward production.
• Design agentic workflows enabling autonomous, auditable experiments.
• Contribute to open-source software, CI/CD, testing and docs.
• Collaborate with universities, labs and international partners.
• Translate domain science needs into scalable workflow and data solutions.
• Publish research and present at conferences.

Skills

Python

Distributed systems

Workflow orchestration

Provenance models

AI agent frameworks

Linux

Communication

Education

PhD in Computer Science

MS in Computer Science

Tools

Flowcept

SLURM

CI/CD

Docker

Job description

Major Duties/Responsibilities

• Provenance and Runtime Data Capture Systems: Contribute to the development of runtime data integration and provenance capture systems (e.g., Flowcept) that instrument distributed scientific workflows, ML training pipelines, and agentic systems. Help implement low-overhead instrumentation and adapters for common execution frameworks, apply provenance data models aligned with community standards (e.g., W3C PROV), and support the query, storage, and streaming layers (e.g., message brokers, document and time-series stores) needed to make workflow telemetry usable at scale.
• Cross-Facility Integration Support: Support ORNL's participation in cross-facility initiatives (e.g., AmSC, Genesis Mission) that build interoperable provenance and workflow-data capabilities spanning leadership computing, experimental facilities, and cloud platforms. Help build services that track data lineage, model artifacts, and computational campaigns across the DOE complex, and assist in coordinating with partner laboratories to align schemas, APIs, and metadata standards so that provenance is portable between facilities. Track milestones and deliverables and contribute to proposals and reports that sustain the portfolio.
• Platform Integration Support: Support OLCF platform efforts (e.g., OPAL) by helping translate scientific and programmatic requirements into deployable system designs. Assist in evaluating architectural trade-offs across orchestration, data management, storage, and security, and work with senior staff and facility operations to help move designs from prototype toward production.
• Agentic Workflow Design and Autonomous Control Systems: Implement components of agentic workflow architectures that enable autonomous, closed-loop scientific experimentation across HPC and instrument facilities. Help integrate agentic frameworks with provenance and orchestration layers so that AI agents can plan, execute, monitor, and adapt multi-step workflows while producing auditable, reproducible records of their decisions and tool use. Apply these patterns to use cases such as autonomous materials discovery, self-steering simulations, and adaptive experimental campaigns.
• Open-Source Software Contribution: Contribute to the technical direction and health of open-source research software, including code review, CI/CD, testing, packaging, documentation, and release support. Help support the external contributor and user community, respond to issues, and help ensure software is deployable beyond ORNL.
• Research Collaboration: Participate in research collaborations with universities, national laboratories, and international partners. Contribute to joint research directions and help convert collaborative work into shared software and publications.
• Scientific Domain Support: Collaborate with domain scientists in areas such as materials science, climate science, and autonomous experimentation to translate research objectives into scalable, automated workflow and data-capture solutions. Provide documentation, training, and direct user support.
• Research and Publication: Conduct research on provenance, workflow systems, orchestration, and data management for AI-driven science, under the guidance of senior staff. Publish in peer-reviewed venues and present at conferences (e.g., SC, HPDC, IPDPS, eScience).

Basic Qualifications

• Ph.D. in Computer Science, Computer Engineering, or a closely related field, or a M.S. or B.S. in a related field with commensurate relevant experience.
• Experience designing or operating distributed systems, provenance frameworks, or workflow orchestration frameworks.
• Familiarity with or exposure to designing agentic workflows or AI agent frameworks.
• At least 1 year of programming experience in Python, with working familiarity in Bash and/or a compiled language (C/C++ or similar).
• Experience with Linux-based HPC environments and familiarity with job scheduling systems (e.g., SLURM or PBS).
• Strong verbal and written communication skills, with the ability to collaborate across technical and scientific teams.

Preferred Qualifications

• Demonstrated experience with provenance models such as W3C PROV.
• Demonstrated experience publishing research in high-impact venues such as SC, IPDPS, HPDC, or IEEE eScience.
• Experience working in or coordinating across DOE national laboratory environments, particularly in the context of integrated or cross-facility research infrastructure.
• Background in scientific data management, provenance tracking, or metadata systems.
• Demonstrated ability to contribute to technical projects and coordinate effectively with multidisciplinary teams.
• Familiarity with basic cyber-security principles (e.g., SSH key hygiene, least privilege, network segmentation) as applied to workflow and API design.

Special Requirements

• For employment at Oak Ridge National Laboratory (ORNL), a Real ID compliant form of identification will be required. Additionally, ORNL is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as mandated by Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which requires a favorable post-employment background investigation.
• To obtain this credential, new employees must successfully complete and pass a Federal Tier 1 background check investigation. This investigation includes a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last year. This includes marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
• For foreign national candidates: If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) risk determination to maintain employment. Once you meet the three-year residency requirement, you will be required to obtain a PIV credential to maintain employment.
• We offer a flexible work environment that supports both the organization and the employee. A hybrid/onsite working arrangement may also be available with this position, which provides flexibility to work periodically from your home, while reporting onsite to the Oak Ridge, Tennessee location on a weekly and regular basis.

About ORNL

As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an impressive 80-year legacy of addressing the nation’s most pressing challenges. Our team is made up of over 7,000 dedicated and innovative individuals! Our goal is to create an environment where a variety of perspectives and backgrounds are valued, ensuring ORNL is known as a top choice for employment. These principles are essential for supporting our broader mission to drive scientific breakthroughs and translate them into solutions for energy, environmental, and security challenges facing the nation.

ORNL offers competitive pay and benefits programs to attract and retain individuals who demonstrate exceptional work behaviors. The laboratory provides a range of employee benefits, including medical and retirement plans and flexible work hours, to support the well-being of you and your family. Employee amenities such as on-site fitness, banking, and cafeteria facilities are also available for added convenience.

Other benefits include the following: Prescription Drug Plan, Dental Plan, Vision Plan, 401(k) Retirement Plan, Contributory Pension Plan, Life Insurance, Disability Benefits, Generous Vacation and Holidays, Parental Leave, Legal Insurance with Identity Theft Protection, Employee Assistance Plan, Flexible Spending Accounts, Health Savings Accounts, Wellness Programs, Educational Assistance, Relocation Assistance, and Employee Discounts.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer.