Berkeley Lab's (LBNL) Environmental Genomics and Systems Biology (EGSB) Division has an opening for an AI Software Engineer to join the US Department of Energy's (DOE) Systems Biology Knowledgebase (KBase) team!
In this exciting role, you will focus on developing software infrastructure for AI-driven scientific workflows, including intelligent agents that interact with KBase's Data Lakehouse and biological knowledge resources. You will have the opportunity to work with KBase's Principal Investigator (PI) and domain scientists, to develop AI agents, co-scientist tools, data services, knowledge graphs, and knowledge representations that enable AI to reason over harmonized biological data. The position emphasizes scalable infrastructure, scientifically rigorous AI-generated insights, and close collaboration with researchers. You will also have opportunities to contribute to peer-reviewed publications and shape next-generation AI-assisted discovery workflows for KBase.
This position has an anticipated start date of September 14, 2026.
***Note: This position is only open to current Berkeley Lab employees. If you are a current Berkeley Lab employee experiencing technical difficulties with submitting your application, please contact [redacted].***
What You Will Do:- Collaborate with the KBase technical lead to design and develop AI agents integrated with KBase interfaces, Apps, and data services.
- Build agent-based tools using Python, LangChain, LangGraph, CrewAI, and modern LLMs.
- Develop AI agents that interact with the KBase Datastore and Delta Lake/PySpark Lakehouse.
- Design agent state management, prompt strategies, and benchmarking to ensure reliability and performance.
- Develop robust, tested software for agent orchestration and workflow integration.
- Collaborate with the AI/ML team on foundational models and tools for microbial genomics.
- Integrate AI capabilities across front-end and back-end systems.
- Develop, test, maintain, and document software following team quality standards.
- Provide technical guidance and mentorship on AI tools and system integration.
What We Are Looking For:- A Bachelor's Degree (or equivalent knowledge/training) in Computer Science, Engineering, Computational Biology, or a related field and a minimum of 5 years of relevant work experience in AI agent frameworks, data engineering, and software development in service of scientific research or an equivalent combination of education and experience.
- Experience designing and implementing intelligent agents for scientific or technical workflows for analyzing biology and environmental data sets.
- Experience working with large language models (LLMs) and prompt engineering across multiple providers.
- Demonstrated experience with PySpark and data engineering using modern lakehouse architectures, including Delta Lake.
- Experience deploying and supporting data- and compute-intensive workflows on high-performance computing (HPC) systems and/or cloud-based research infrastructure.
- Demonstrated proficiency in Python and AI agent frameworks, including LangChain, LangGraph, and CrewAI.
- Familiarity with machine learning libraries, such as PyTorch, TensorFlow, and Scikit-learn.
- Knowledge of open-source collaboration, including GitHub workflows and Agile practices.
- Strong understanding of AI agent architecture, including agent state management, evaluation, and benchmarking.
- Demonstrated analytical and problem-solving skills, including the ability to identify, troubleshoot, and resolve technical problems of diverse scope where analysis of data requires evaluation of identifiable factors.
- Excellent oral and written communication skills, including the ability to organize and present technical information effectively to both technical and non-technical audiences.
- Demonstrated interpersonal and collaboration skills, including the ability to work effectively with a variety of scientific, operations, and technical teams.
Desired Qualifications:- A Master's Degree (or equivalent knowledge/training) in Computer Science, Engineering, Computational Biology, or a related field and a minimum of 3 years of relevant work experience in AI agent frameworks, data engineering, and software development in service of scientific research or an equivalent combination of education and experience.
- Experience with scientific reproducibility practices and metadata standards.
- Familiarity with scientific data analysis and visualization techniques.
Additional Information:- Application Date: Priority consideration will be given to candidates who apply with a resume and a cover letter by September 7, 2026. Applications will be accepted until the job posting is removed.
- Appointment Type: This is a full time, exempt from overtime pay (monthly paid), 1 year (benefits eligible), 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 Information: This position has a budgeted salary range of $117,132 - $146,400 annually, for job code C70.2. It is not typical for an individual to be offered a salary at or near the top of the budgeted range for a position. Salary for this position will be commensurate with the final candidate's qualification and experience, including skills, knowledge, relevant education, certifications, and aligned with the internal peer group.
- 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: This position will be performed onsite at Lawrence Berkeley National Lab located at 1 Cyclotron Road, Berkeley, CA 94720. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here).
Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov
