Lawrence Berkeley National Laboratory’s (LBNL) Scientific Networking Division has an immediate opening for a Full Stack, Python focused Software Engineer to join Energy Sciences Network (ESnet) on the Orchestration and Core Data team. The Orchestration and Core Data team is a small, collaborative group of engineers that provide innovative network management solutions designed to orchestrate and automate service deployment, device management, and ongoing operations of the ESnet network. Remote work is an option.

In this exciting role, you will contribute to the design, development, operation, and maintenance of robust, mission-critical software solutions, providing technical guidance to peers and ensuring reliable service delivery.

You will:

Build, operate, and maintain backend/frontend components for network orchestration, databases, and web applications.
Ensure production systems are reliable, scalable, and secure using sound engineering practices.
Collaborate with stakeholders and support users throughout the product lifecycle.
Design and implement accessible, high-performance web interfaces using UX/UI best practices and tools like Figma.
Leverage open-source and internal frameworks to improve network operations.
Analyze complex problems and develop maintainable software from user stories, specifications, and designs.
Mentor teammates, coordinate assignments, and foster a collaborative team culture.
Contribute to automation, orchestration, and network operations solutions across projects.

We are looking for:

Bachelor’s degree and 8 years of related experience, or advanced degree and 6 years; or an equivalent combination of education and experience.
Experience with application development in Linux environments using Python and JavaScript.
Exposure to scalable systems, interfaces, and data models.
Strong problem-solving and analytical skills.
Ability to work effectively in collaborative, interdisciplinary teams.
Application development skills with Python and JavaScript.
Understanding of data structures and algorithms.
Familiarity with web APIs such as GraphQL, REST, and SOAP.
Ability to deliver solutions on time and within project constraints.
Excellent written and verbal communication skills.

Desired skills/knowledge:

Experience developing automated deployment systems or network management software.
Familiarity with Django, SQLAlchemy, FastAPI, ReactJS/NextJS, GraphQL.
Solid proficiency with Django, SQLAlchemy, or other Python frameworks.
Understanding of REST and GraphQL-based API solutions.
Proficiency in Java and the Spring framework.
Experience with Docker or Kubernetes.
Proficiency in frontend development in next.js, React, or other similar framework.
Familiarity with Agile/Scrum, testing, source code management (Git/GitHub), and release procedures.

We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

Why join Berkeley Lab?

We invest in our employees by offering a total rewards package you can count on:

Exceptional health and retirement benefits, including pension or 401K-style plans
A culture where you’ll belong - we are invested in our teams!
In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
Parental bonding leave (for both mothers and fathers)
Pet insurance

Additional information:

Application date: Priority consideration will be given to candidates who apply by August 20, 2026. Applications will be accepted until the job posting is removed.
Appointment type: This is a full-time 2-year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
Salary range: The expected salary for this position is $156,864 - $191,724, which fits into the full salary of $139,440 - $235,308 depending upon the candidate’s skills, knowledge, and abilities. This includes education, certifications, and years of experience.
Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
Work modality: Work may be performed on-site, hybrid, full-time telework. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).
Work authorization: Candidates must be eligible to work in the U.S. at the time of hire.

Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, protected veteran status, or other protected categories under State and Federal law.

Misconduct Disclosure Requirement: As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer. For additional information, click here.