Full Stack Engineer (Python Focussed)

Lawrence Berkeley National Laboratory (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.

CSE3 candidates will apply wide-ranging expertise to 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:

• Contribute to building, operating, and maintaining backend and frontend network orchestration, database, and web applications.

• Ensure reliability, scalability, and security of production systems, applying sound judgment in selecting methods and approaches.

• Collaborate with stakeholders and guide users through the full product lifecycle, building relationships with peers and contacts across technical areas.

• Apply UX/UI design principles and implement accessible, performant web interfaces using tools like Figma.

• Leverage open-source and internal frameworks to support network operations.

• Independently analyze complex issues, evaluate multiple factors, and write maintainable software based on user stories, specifications, and designs.

• Mentor peers, coordinate activities on new assignments, and contribute to a growth-oriented team culture.

• Contribute to solutions that enhance service automation, orchestration, and network operations within assigned projects.

We are looking for:

• Typically requires a Bachelor's degree and 8 years of related experience, or advanced degree and 6 years; or an equivalent combination of education and experience.

• Wide-ranging expertise with software development 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.

• Linux 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.

• 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:

• 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.

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.

Berkeley Lab is a University of California employer. It is the policy of the University of California to undertake affirmative action and anti-discrimination efforts, consistent with its obligations as a Federal and State contractor.

Misconduct Disclosure Requirement: As a condition of employment, the finalist will be required to disclose if they are subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct, are currently being investigated for misconduct, left a position during an investigation for alleged misconduct, or have filed an appeal with a previous employer.